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Organization Science

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Blurring the Boundaries The Interplay of Gender andLocal Communities in the Commercialization of SocialVentureshttporcidorg0000-0003-4699-4832Stefan Dimitriadis httporcidorg0000-0003-4772-130XMatthew Lee httporcidorg0000-0002-9979-5354LakshmiRamarajan Julie Battilana

To cite this articlehttporcidorg0000-0003-4699-4832Stefan Dimitriadis httporcidorg0000-0003-4772-130XMatthew Lee httporcidorg0000-0002-9979-5354Lakshmi Ramarajan Julie Battilana (2017) Blurring the Boundaries The Interplay of Genderand Local Communities in the Commercialization of Social Ventures Organization Science

Published online in Articles in Advance 23 Aug 2017

httpsdoiorg101287orsc20171144

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ORGANIZATION SCIENCEArticles in Advance pp 1ndash21

httppubsonlineinformsorgjournalorsc ISSN 1047-7039 (print) ISSN 1526-5455 (online)

Blurring the Boundaries The Interplay of Gender and LocalCommunities in the Commercialization of Social VenturesStefan Dimitriadisa Matthew Leeb Lakshmi Ramarajana Julie Battilanaa

aOrganizational Behavior Unit Harvard Business School Boston Massachusetts 02163 b Strategy Unit INSEAD Singapore 138676Contact sdimitriadishbsedu httporcidorg0000-0003-4699-4832 (SD) matthewleeinseadedu

httporcidorg0000-0003-4772-130X (ML) lramarajanhbsedu httporcidorg0000-0002-9979-5354 (LR) jbattilanahbsedu (JB)

Received May 28 2015Revised July 13 2016 March 14 2017Accepted April 3 2017Published Online in Articles in AdvanceAugust 23 2017



Abstract This paper examines the critical role of gender in the commercialization of socialventures We argue that cultural beliefs about what is perceived to be appropriate workfor each gender influence how founders of social ventures incorporate commercial activityinto their ventures Specifically we argue and show that although cultural beliefs thatdisassociate women from commercial activitymay result in female social venture foundersbeing less likely to use commercial activity than their male counterparts these effects aremoderated by cultural beliefs about gender and commercial activity within foundersrsquo localcommunities The presence of female business owners in the same community mitigatesthe role of foundersrsquo gender on the use of commercial activity We examine these issuesthrough a novel sample of 584 social ventures in the United States We constructivelyreplicate and extend these findings with a supplemental analysis of a second samplethe full population of new nonprofit organizations founded during a two-year period inthe United States (n 31160) By highlighting how gendered aspects of both the socialand commercial sectors interact to shape the use of commercial activity by social venturefounders our findings contribute to research on hybrid organizations in the social sectorcommunities as a context for the enactment of gender and the enactment of gender inentrepreneurship

Supplemental Material The online appendix is available at httpsdoiorg101287orsc20171144

Keywords social venture bull gender bull community bull commercialization bull cultural beliefs

IntroductionThe US social sector has from its founding distin-guished itself from the commercial sector by its useof voluntary noncommercial means to pursue its civicgoals (de Tocqueville 2012) The last 30 years how-ever have seen social sector organizations increasinglyutilize commercial practices that earn revenue thusblurring the traditional boundaries between the two(Powell et al 2005 Smith and Lipsky 1993) This trendof commercialization follows declines in the chari-table resource environment (Defourny and Nyssens2006 Eikenberry and Kluver 2004 Kerlin 2006) and theimportation of business practices by managerial pro-fessionals moving into the social sector (Hwang andPowell 2009 Skocpol 2003) Commercialization is evi-dent not only in existing social sector organizationsbut in the creation of new hybrid social ventures thatpursue a social mission while engaging in commer-cial activity to sustain their operations Such venturesblend aspects of the social and commercial sectorsresulting in hybrid organizational arrangements thatcombine aspects of typical businesses and nonprof-its (Battilana and Lee 2014 Besharov and Smith 2014Pache and Santos 2013)

Hybrid social ventures possess multiple differingsets of goals andmotivations associated with the socialand commercial sectors They consequently experiencetensions between their social and commercial activitiesthat complicate organizational functioning (Battilanaet al 2015) Traditionally social welfare goals and aspirit of voluntarism have motivated the activity ofsocial sector organizations (Frumkin 2002) By con-trast efficiency and the maximization of profits haveprimarily determined the activity of commercial sec-tor organizations Intriguingly these sectoral distinc-tions parallel differences in cultural beliefs about thetypes of work considered to be appropriate for womenand men Gendered cultural beliefs associate womenwith personal qualities such as caring selflessnessand communalism (Eagly and Steffen 1984) attributesthat are consistent with the goals and motivations ofthe social sector Men on the other hand are seen tobe stereotypically competitive risk taking and agen-tic (Eagly and Karau 2002 Heilman et al 1989 Lucas2003) attributes consistent with the goals and moti-vations of the commercial sector Hence the normsthat have traditionally guided the social and commer-cial sectors mirror cultural beliefs about appropriatebehaviors for women and men respectively

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Dimitriadis et al Blurring the Boundaries2 Organization Science Articles in Advance pp 1ndash21 copy2017 INFORMS

Despite evidence of the prevalence in the socialsector of gendered feminine norms (McCarthy 2001Themudo 2009) and the distinctive role therein offemale professionals (Halpern 2006 Odendahl andOrsquoNeill 1994) surprisingly little research has examinedthe relationship between gender and commercializa-tion of the social sector We shed light on this issueby examining the relationship between the gender ofsocial entrepreneurs and their use of commercial activ-ity at the time of a social venturersquos founding Build-ing on previous scholarship about how cultural beliefsabout gender shape individual behavior (Ridgewayand Correll 2004) we theorize that female founders ofsocial ventures will be less likely than male founders touse commercial activity in their social ventures becauseof prevailing cultural beliefs that associate commercialactivity with men

Drawing on a conception of gender as a multi-level construct whereby the effects of gendered cul-tural beliefs depend on the social relational context(Ely and Padavic 2007 Ridgeway and Correll 2004)we further argue that the enactment of cultural beliefsabout what is appropriate behavior for women andmen will differ according to the social relational con-text in which the social venture founder is embeddedWe focus on geographic communities as an impor-tant social relational context for gender enactmentin social venture founding because they have beenfound to be important arenas of interaction for dif-ferent types of organizations (Marquis and Battilana2009) including commercial (Marquis and Lounsbury2007) entrepreneurial (Saxenian 1996) and social sec-tor organizations (Galaskiewicz et al 2006) We pro-pose that a key gendered characteristic of communitiesthat may shape female social venture foundersrsquo use ofcommercial activity is the presence of female businessowners who are uniquely positioned to weaken cul-tural beliefs disassociating women from commercialactivity because they are situated at the intersection ofcommunity and business (Brush 1992) We thereforehypothesize that a greater presence of female businessowners within a geographic community will attenuatethe influence of cultural beliefs on female social ven-ture foundersrsquo use of commercial activity

We empirically test our hypotheses using a noveldata set of 584 nascent social ventures based in theUnited States in 2007 and 2008 Consistent with ourhypotheses we find that social ventures founded bywomen are less likely to engage in commercial activ-ity but that this effect is significantly diminished ingeographic communities where there is a greater pres-ence of female business owners To complement andextend our main analysis we conduct a constructivereplication (Lykken 1968 Eden 2002) using the fullpopulation of 31160 nonprofit organizations foundedin the United States from 2001 through 2003 and find

results consistent with our hypotheses This analysisof nonprofit entrepreneurshipmdasha separate setting inwhich similar dynamics of commercialization and gen-der are presentmdashoffers further support for our theo-retical arguments Additional analyses of the survivalof these nonprofit ventures further show that women-led nonprofits that use commercial activity experiencea higher risk of failure in the first five years of theirexistence

Our paper makes three main contributions Firstalthough emerging research examines the drivers ofhybrid organizations that combine aspects of the socialand commercial sectors (Battilana and Lee 2014) ourstudy speaks to the critical but often overlooked roleof gender in understanding this trend Specifically itillustrates how the hybridization of an organizationalpopulation can be associated with cultural beliefsabout appropriate behaviors for women and men Webring to the fore the intersection of gendered beliefsabout commercial activity and gender representationin local business sectors to show how these jointly rein-force or disrupt cultural beliefs about gender and com-mercial activity Our study thus illustrates a multilevelmechanism by which cultural beliefs about genderdifferences influence how organizational populationschange and identifies how situated gender enactmentsexplain differences in participation in that change

Second building on conceptions of gender as a mul-tilevel construct enacted in local contexts (Ely 1995Ridgeway and Correll 2004) we show how culturalbeliefs about gender differences shape entrepreneurialbehavior within geographic communities While com-munities play an increasingly important role in organi-zation and management theory (Marquis 2003 Tilcsikand Marquis 2013) relatively little is known abouttheir connectionwith gendered cultural beliefs Emerg-ing work hints at the role of geographic community-based gender norms in shaping organizational found-ing (Theacutebaud 2015) survival (Kalnins and Williams2014) and performance (Post and Byron 2015) Ourwork extends this line of inquiry by considering howcommunity-level norms about the appropriateness ofcommercial activity for each gender may shape gen-dered behavior in organizations

Last research on gender and entrepreneurshiphas made major advances in identifying inequalityin entrepreneurial behavior and the mechanisms bywhich it is sustained (Kacperczyk 2013 Renzulli et al2000 Yang and Aldrich 2014) but it has found mixedresults about whether female and male entrepreneursuse different organizational activities in their ventures(Jennings and Brush 2013) Our theoretical frameworkwhich proposes that the use of organizational activ-ities depends on gendered cultural beliefs in localsocial relational contexts may account for some ofthe mixed findings in the literature on gender and

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Dimitriadis et al Blurring the BoundariesOrganization Science Articles in Advance pp 1ndash21 copy2017 INFORMS 3

entrepreneurship Ultimately our work offers a theo-retical lens as well as multiple empirical tests throughwhich to begin understanding how gender affects com-mercialization in the social sector

Commercialization in the Social SectorThe social sector consists of private organizations thatexplicitly attempt to improve society and is distinctfrom both the public and business spheres (DiMaggioand Anheier 1990 Salamon and Anheier 1997) Wefollow previous research in defining social venturesas newly founded organizations in the social sector(Moss et al 2011 Sharir and Lerner 2006) Social ven-tures pursue social missions addressing a variety ofsocial problems (eg poverty alleviation education)while sharing the feature that social benefit is core totheir organizational identities (Grimes 2010 Moss et al2011) and strategic decision making (Austin et al 2006Dees 1998)Social ventures have traditionally followed a char-

ity model of organizing (Ott and Dicke 2001 Powelland Steinberg 2006) that draws on a constellation ofresource providers who voluntarily commit resourcesto the charitable organization (Bryson 1988) The socialsector is thus made up of charitable organizationsand their founders as well as sector-specific resourceproviders that include professionals charitable foun-dations and private donors (Frumkin 2002) The socialsector and its organizing principles are further legiti-mated by formal regulatory structures that allow socialsector organizations to self-elect as providing publicbenefit for instance ldquopublic charitiesrdquo receive relieffrom taxation with the limitation that leaders of theorganizationmay not profit financially from their activ-ity (Hansmann 1980) Such institutional constraints tra-ditionally provide social sector organizations with adistinctive identity and ostensibly ensure the integrityof the social sector (Hall 2006)

An increasing number of social ventures howeverengage in commercial activity to financially sustaintheir operations thereby diverging from the tradi-tional charity model (Kerlin and Pollack 2011) Suchhybrid social ventures engage in ldquoenterprisingrdquo prac-tices normally associated with businesses (Light 2008)and enter into existing commercial markets (Battilanaet al 2012 Foster and Bradach 2005 Young 2009) Com-mercialization may involve peripheral business activ-ity unrelated to the social venturersquos mission but com-mercial activity may also advance the social venturersquossocial mission (Dees 1998) For instance organizationsmay train unemployed or underemployed individualsin a craft and sell their products to generate revenuethat sustains the organization (Battilana et al 2015)To create such ventures however entrepreneurs mustovercome significant institutional boundaries such asthe existence of separate legal structures for nonprofit

and commercial organizations as well as institutional-ized sector-specific financing structures (Battilana andLee 2014 Dees 1998)

Recent research examines the particular organiza-tional challenges and opportunities raised by the com-mercialization of social ventures On the one handthose social ventures that pursue a social missionthrough commercial activity are frequently cited ascases of organizational innovation that align with thefoundersrsquo personal values (Fauchart and Gruber 2011Wry and York 2017) while also enabling institutionalchange (Jay 2013) On the other hand they also facedistinct organizational challenges including resourceallocation trade-offs between commercial activity andactivity that directly advances their social missionsleading in some cases to organizational failure (Traceyet al 2011) New social ventures also struggle to rec-oncile cultural differences among organization mem-bers particularly their relative orientations toward thesocial and commercial activity of the organization(Almandoz 2014 Battilana and Dorado 2010)

Previous studies of commercialization in the socialsector have emphasized both strategic and culturalperspectives A frequently cited model advanced byWeisbrod (1998) argues that commercialization is theoutcome of joint optimization of (i) the production ofpublic goods that advance the social mission (ii) pri-vate goods that advance the social mission and (iii)revenue-generating activity that enables the later pro-vision of private goods The decision to commercial-ize therefore follows from environmental and tech-nological differences that affect the opportunities anddistribution structures associated with these optionsOther studies have emphasized alternative explana-tions including the strategic benefit of managing riskrelated to uncertain charitable funding (Dees 1998)declining institutional boundaries between the socialand business sectors (Townsend andHart 2008) as wellas increased cultural rationalization across all organi-zations (Bromley and Meyer 2015) We are unawarehowever of any research that has examined the role ofcultural beliefs about gender differences in the use ofcommercial activity in the social sector

A Multilevel View of Gender andCommercializationGender is a multilevel system of broadly held culturalbeliefs regarding appropriate behavior for women andmen that is enacted by individuals and is mani-fested in everyday interactions as well as in societal-level processes (Ridgeway and Smith-Lovin 1999Martin and Ruble 2004) Cultural beliefs about genderare not unvarying but rather are activated by socialrelational context (Ridgeway 2009) Social relationalcontexts are arenas in which individuals interact and

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define themselves in relation to others in ways thatcan reinforce or disrupt cultural beliefs about genderand thus affect behavior (Correll 2001 2004 Ridgewayand Correll 2004 Ridgeway and Smith-Lovin 1999Theacutebaud 2010)Cultural beliefs about gender associate different lev-

els of competence with women and men in the com-pletion of specific tasks and activities (Cejka and Eagly1999) Consequently ldquooccupations and activities aswell as people have gender identitiesrdquo (Kirkham andLoft 1993 p 511) In other words particular tasksand activities are gender-typed (Ashcraft 2013 Chanand Anteby 2016 Cohen and Bunker 1975) Consider-able evidence suggests that commercial activity is pre-dominantly male-typed Prevailing images of success-ful businesspeople are predominantly male (Jenningsand Brush 2013 Schein 2001) based on a ldquothinkmanager-think malerdquo schema (Schein 2001 p 675Sczesny 2003 p 353) Such images associate menwith traits and behaviors that suggest commercial suc-cess such as competitiveness agency and self-interestwhile perceiving women as other-interested warmcaring and givingmdashcharacteristics aligned with char-itable and noncommercial work Although culturalbeliefs about gender are being gradually redefinedin many parts of the world this prevailing schemastill discourages women from undertaking commer-cial activity (England 2006 Haveman and Beresford2012 Ridgeway 2011) notwithstanding increasing full-time employment among women (Cuddy et al 2004Hochschild and Machung 1989 Stone 2007)

Cultural beliefs that disassociate women from com-mercial activity may affect womenrsquos participation incommercial activity through two mechanisms that aremutually reinforcing First cultural beliefs about gen-der can lead to self-evaluation and self-stereotypingmdashie under certain conditions women themselves adoptprevailing schema and therefore view themselves asincapable of or aversive to commercial activity andconsequently favor noncommercial work that is morealigned with cultural beliefs about gender and work(Atwater et al 2004 Marini and Brinton 1984) Sec-ond such beliefs can lead others to evaluate negativelywomen who engage in commercial activity Researchsuggests that gendered cultural beliefs lead to socialbacklash (and consequently penalties) against agen-tic women or women who undertake masculine-typedactivity (Rudman and Phelan 2008) Thus the influenceof cultural beliefs on women and on those who evalu-ate them leads women away from commercial activityrelative to men

Cultural beliefs about gender manifest in many as-pects of entrepreneurship such as lower aspirationsand expectations for the commercial success of femaleentrepreneursrsquo ventures (Buttner and Rosen 1992Marlow and Patton 2005 Theacutebaud 2010) While little is

known regarding women entrepreneursrsquo use of com-mercial activity in social ventures evidence does showother effects of gendered cultural beliefs including apersistently lower likelihood to found a commercialbusiness (Ding et al 2013 Kalleberg and Leicht 1991Ruef et al 2003) lesser access to resources (Greene et al2001 Renzulli et al 2000) and increased experiences ofdiscrimination (Brooks et al 2014 de Bruin et al 2007Kaplan and Vanderbrug 2014 Theacutebaud and Sharkey2016) Moreover studies show that even when womenfound businesses these are shaped by cultural beliefsrelated to gender For instance they are more likely tostart companies in care- and service-based industriessuch as retail and personal services which are asso-ciated with feminine gender norms and less likely tostart companies in more explicitly commercial indus-tries such as finance which are associated with mas-culine gender norms (Robb and Watson 2012)

The use of commercial activity by social venturefounders however remains an open and complexquestion because the social sector is more stronglyfemale-typed compared to the sectors studied anddescribed above Indeed much work in organizationalbehavior on women engaging in stereotypically mas-culine tasks and activities arises from the emphasisof previous research on women in male-dominatedprofessions (Billing 2011 Blair-Loy 1999 Ely 1995Kanter 1977 Reskin and Roos 1990) However littlework on organizational behavior and gender has exam-ined womenrsquos engagement in stereotypically mascu-line activities in female-typed occupations and sec-tors Interestingly Rudman and Glick (2001) found ina lab setting that women seeking feminine occupationsfaced greater backlash when they engaged in agen-tic behavior because it was seen as a greater violationof gender norms By contrast women seeking mascu-line occupations faced pressure to engage in agenticbehavior so that their qualifications would not be dis-regarded even though they may receive some penaltyfor being less likeable

Building on this idea we argue that in the socialsector cultural beliefs about the appropriateness ofengaging in commercial activity for women are likelyto be amplified for at least two reasons First cul-tural beliefs about gender are considered socially validwhen individuals observe those around them acting inaccordance with those cultural beliefs (Ridgeway andCorrell 2006 Ridgeway et al 2009) Since the social sec-tor is predominantly female and also predominantlyoperates under the traditional charity model it pro-vides social validation of the appropriateness of char-itable activity for women while also socially validat-ing the inappropriateness of commercial activity forwomen This pronounced social validation of genderedcultural beliefs about commercialization in the socialsector is likely to amplify the impact of the beliefs on

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foundersrsquo actions Second because the traditional char-ity model is female-typed women who engage in char-itable activities are likely to be seen as more competentin those activities and consequently less likely to facebacklash than those engaged in commercial activity Asa result female social venture founders may be morelikely to identify with and defend the charity modelthan men (Fantasia and Hirsch 1995 Kellogg 2009)We therefore expect to find a significant effect of

gender on the use of commercial activity ie thatfemale founders are less likely to incorporate commer-cial activity in their venturesWhile this effect is consis-tent with women avoiding commercial activity for fearof backlash (Rudman and Phelan 2008) and harsherself-assessments (Theacutebaud 2010) in male-dominatedsettings this effect may be amplified in the social sec-tor where commercial activities engaged in by womenwill be viewed as particularly misaligned with sociallyvalidated views of womenrsquos work Given the effects ofcultural beliefs about gender and commercial activityas well as the compounding effect of operating in afeminine sector we expect female social entrepreneursto be less likely to use commercial activity We there-fore hypothesize the following

Hypothesis 1 Female social venture founders are lesslikely to incorporate commercial activity in their social ven-tures than male social venture founders

Gender and Commercial Activity in LocalCommunities Female Business OwnersAlthough cultural beliefs about gender are pervasivetheir enactment varies depending on different socialrelational contexts (Ely and Padavic 2007 Martin 2000Ridgeway 2011 West and Zimmerman 1987) A partic-ularly salient social relational context for social venturefounders is likely to be the local geographic commu-nity in which organizations and individuals from thesocial and commercial sectors interact (Galaskiewiczand Burt 1991) and which fundamentally shapes newventures (Piore and Sabel 1984 Saxenian 1996) Socialventures in particular are likely to be embedded intheir local communities because of close relationshipswith beneficiaries who are often local (Groslashnbjerg andPaarlberg 2001 Skocpol 2003) and through their con-tributions to locally shared public goods in whichcommunity members have an interest (Molotch 1976Putnam 2000) In addition social ventures engage inextensive and repeated interactions with business andgovernment organizations in their local communitiesto gain resources that are critical to their survival(Galaskiewicz et al 2006 Pfeffer 1973 Walker andMcCarthy 2010)Because local communities are important places

where the social and business sectors interact it isimportant to examine the enactment of gendered cul-tural beliefs regarding commercial activity within local

communities One specific characteristic of communi-ties that may shape gendered cultural beliefs regardingcommercial activity is the presence of female businessowners Female business owners are uniquely situatedat the intersection of local communities and the busi-ness sector (Brush 1992 McGregor and Tweed 2002)and thus can affect cultural beliefs about gender withinthese communities that is female business ownersmay be influential not just within the business sectorbut also within the community at large and thus theirimpact may spill over to influence women in the socialsector as well

The presence of female business owners within alocal community is likely toweaken cultural beliefs dis-associating women from commercial activity Researchsuggests that occupations tasks and activities areoften defined by the ascribed characteristics or socialidentities of those who perform those tasks and activ-ities (Ashcraft 2013 Kirkham and Loft 1993) As theproportion of women or men engaged in a taskchanges cultural beliefs regarding who is appropriateto engage in the task can be weakened (Reskin andRoos 1990 Ridgeway and England 2007) For instancestudies show that as women entered certain occupa-tions in greater numbers such as teaching culturalbeliefs associating men with these occupations even-tually shifted toward these occupations being seen asfemale-typed (Irvine and Vermilya 2010 Richardsonand Hatcher 1983) Taken together these findings sug-gest that as the presence of female business owners inthe local geographic community grows cultural beliefsthat disassociate women from commercial activitieswithin that community can become weaker

Building on this research we argue that the weaken-ing of gendered cultural beliefs within a communitymdashalbeit due to forces outside the social sectormdashwill affectthe use of commercial activity by female social ven-ture founders for three reasons First in communi-ties with numerous female business owners femalesocial venture founders who engage in commercialactivity will be less likely to be perceived as violat-ing cultural beliefs about gender (Diekman and Eagly2000 Ridgeway 2001) They will therefore be less likelyto anticipate backlash and this will in turn shapetheir behavior (Rudman and Phelan 2008) Secondthey may be less likely to self-stereotype by under-estimating their own abilities and minimizing theirdesire to pursue commercial activity (Beaman et al2012 Dasgupta 2011) Evidence suggests that as theproportion of women leaders engaged in masculineactivities in male-dominated settings increases cul-tural beliefs about gender are less likely to guide indi-vidual womenrsquos self-assessments and behavior lowerin the hierarchy (Ely 1995) Last to the extent that com-mercial activity is seen less as a masculine preserve ina given community women who engage in it may be

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judged as more competent Thus female social venturefounders in communities with a greater presence offemale business owners may also be less likely to iden-tify with and defend the charity model and be moreopen to demonstrating competence through commer-cial activity as wellIn Hypothesis 1 we argued that cultural beliefs

about the male-typing of commercial activity partic-ularly in the social sector will limit the commercial-ization of social ventures founded by women Herewe further propose that female business owners inlocal communities play a role in moderating this trendie a higher proportion of female business ownersin a community has the potential to weaken culturalbeliefs that disassociatewomen from commercial activ-ity and thus moderate female social venture foundersrsquouse of commercial activity We therefore hypothesizethe following

Hypothesis 2 Female social venture founders in commu-nities where a higher proportion of business owners arefemale are more likely to incorporate commercial activityin their social ventures than other female social venturefounders

Methods and AnalysisWe tested our hypotheses on a sample of 584 nascentsocial ventures and their founders Data were obtainedfrom a random sample of all applications to a promi-nent fellowship competition for nascent social venturesduring the period 2007 to 2008 All applications forthis fellowship were generated from an annual solicita-tion open to any founder of a social venture Venturesselected for the fellowship received funding to coverthe founderrsquos living costs for two years while the indi-vidual worked on their venture Examples of organiza-tions awarded this fellowship in the past include Teachfor America an organization that places recent collegegraduates in teaching positions in low-income com-munities and Carbon Lighthouse an organization thatprovides technological services to consumers and cor-porations to help them reduce their carbon footprintOur sample however includes not only eventual win-ners of the fellowship but also applicants who werenot selected as detailed belowThe social ventures in our sample all pursued an

explicit social mission were independent organiza-tions and were no more than two years old Norequirements limited the strategies of the new venturesor their financing models As a result our samplingframe placed no restrictions or particular guidancerelated to the use of commercial activity and thus iswell-suited to testing factors explaining variation in theuse of commercial activity Furthermore because oursampling frame captures ventures at a nascent stageof development there was relatively little influence

of subsequent external pressure or survivorship biasa common shortcoming in research on entrepreneurdecisions (Katz and Gartner 1988 Theacutebaud 2010)

Our analysis was based on a sample of 584 US-based social ventures spanning 104 communities in 44states We determined this sample as follows Fromall applications received during 2007 and 2008 weselected a random sample of 50 or 1125 applicationsfor in-depth coding and analysis Of these applications722 were based in the United States and 667 of thesecontained sufficient address information to determinetheir geographic location which we accomplished bygeolocating the addresses of the social venture appli-cants with ArcGIS a geographic information systemmapping software Based on the geographic locationwe matched each venture to a Core Based Statisti-cal Area (CBSA) CBSAs include an urban center andsurrounding areas that are socially and economicallyintegrated with it and are a common way of opera-tionalizing geographic communities in the US context(Marquis 2003Marquis et al 2013 Stuart and Sorenson2003) Social ventures located outside defined CBSAswere considered to be outside well-defined commu-nities and were therefore not included in the finalsample

Dependent VariableOur dependent variable commercial activity is a five-point scale that measures the degree to which a ven-ture uses commercial activity A score was assignedto each venture based on in-depth coding of rich textdescriptions of that venture These descriptions weregenerated by the founders and collected via the fel-lowship application process Through a series of open-ended questions applicants were asked to provideinformation about the organizationrsquos mission specificactivities and services approaches to measuring socialimpact and funding model Each application includ-ing the detailed descriptions of ventures spanned 5 to10 pages

Our coding of these descriptions followed a multi-step process First two of the authors conducted a pilotcoding of several hundred applications Second basedon this pilot and a second round of in-depth manualcoding of 10 of the sample the first author developeda coding manual and procedure to assess the degree towhich a proposed venture relied on commercial activ-ity to generate revenues Specifically we developed afive-point scale of commercialization ranging from 1for projects that relied exclusively on noncommercialsources of revenue to 5 for projects that relied exclu-sively on commercial sources of revenue Table A1 inthe online appendix provides examples of projects fordifferent levels of commercialization In the third steptwo external coders then used this scale to assess thelevel of commercialization of each of the social ven-tures in the sample The intercoder reliability among

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the two coders using Krippendorffrsquos alpha was 092indicating a high level of agreement among the coders(Landis and Koch 1977) Differences in coding wereresolved by discussing the application essays until aconsensus was reached (Larsson 1993)

Independent VariablesFemale Gender All applicants were asked to statetheir gender in their applications which was usedto construct a dummy variable for the gender of thefounder Female gender was coded as 1 for applicantsself-identifying as female and 0 for male The variableappears as female founder in the modelsCommunity Female Business Ownership We con-structed a measure of community female businessownership by counting the proportion of businesseswith a payroll located in the corresponding CBSAthat were majority-owned by women This measurewas mean centered We collected these data fromthe US Census Bureaursquos (2007) ldquoSurvey of BusinessOwners and Self-Employed Persons (SBO)rdquo a nationalestablishment-level survey of 23 million randomlyselected businesses conducted every five years Thissurvey is the most comprehensive source of informa-tion about the demographics of business ownershipin the United States Because the survey is conductedonly every five years direct measures for this variablewere unavailable for the year 2008 however from 2002to 2007 the average magnitude of change in the pro-portion of businesses owned by women in each CBSAwas only 11 of business owners increasing our con-fidence that the 2007 measure was appropriate for usewith our full sample

Control VariablesWe included several variables in our models to controlfor possible community- project- and individual-levelpredictors of commercialization At the communitylevel a founderrsquos choice to use commercial activ-ity may depend in part on the local availability ofalternative sources of funding (Groslashnbjerg 1991) Toaccount for such supply-side arguments we devel-oped three control variables based on funding patternsamong nonprofit organizations for each community-year These included charitable giving per capita mea-sured as the dollar amount of donations to public char-ities in the social venturersquos CBSA in the associatedyear divided by its population the proportion of com-mercial nonprofits charities that earned the majority oftheir income from commercial activity and the pro-portion of government-funded nonprofits charities thatreceived at least one government grant Informationfor these variables was collected from the NationalCenter for Charitable Statistics at the Urban Institute(2014) which compiles information on the revenuesand their sources for 501(c)(3) nonprofits from their

annual filings of Internal Revenue Service (IRS) Form990 We also controlled for the population and incomeper capita of each community based on data collectedby the Bureau of Economic Activity for the RegionalEconomic Accounts data series We used the naturallog of these two variables to account for skewed distri-butions

At the project level we included fixed effects corre-sponding to the area of social action of the project notingthat certain types of social problems might be moreamenable to commercialization (Dees 1998) In eachapplication founders declared the social issue thattheir project addressed These areas include ldquoarts cul-ture and humanitiesrdquo ldquocivil and human rightsrdquo ldquoeco-nomic developmentrdquo ldquoeducationrdquo ldquoemploymentrdquoldquoenvironmentrdquo ldquofood nutrition and agriculturerdquoldquohealthrdquo and ldquohousingrdquo We further controlled forwhether the applicant was a member of a team sincethese applicants may have been influenced by theirpartners in the applications Finally we controlled forwhether the project had local beneficiaries to account forthe extent to which beneficiaries were geographicallyproximate to the founder

At the individual level we included controls relatedto each founderrsquos prior exposure to commercial prac-tices through work experience education and raceWe included an indicator variable corresponding towhether the founder worked in a for-profit organization atthe time the application was submitted With regard toeducation we controlled for the founderrsquos level of educa-tional attainment using dummy variables for each pos-sible level of attainment Furthermore we included adummy variable for whether the individual received adegree in business or economics The information on thelevel of education and the subject studiedwas obtainedfrom the application forms Finally to control for pos-sible effects of founder ethnicity on commercializationwe included an indicator variable corresponding towhether the applicant wasAfrican American the largestethnic minority group in our data

EstimationWe estimated our models using a multilevel mixed-effects ordinal logistic model This model takes intoaccount the structure of the discrete ordered depen-dent variable and the two-level nested structure of thedata where each individual founderndashsocial venture isnested within a community This approach estimatesfor each community a unique intercept which controlsfor unobserved community factors and accounts forthe correlated error structure within communities andrelated to cross-level interactions We also includedyear fixed effects to account for potential year effectson the use of commercial practices Table 1 presentsthe summary statistics and the correlation matrix forthe variables in all of the models To test for possi-ble multicollinearity among regressors we estimated

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eser

ved


Table1

SummaryStatistic

sfor

Sampleof

Social

Ventures

Mean

SD

12

34

56

78

910

1112

13

1Co

mmercia

lactivity

186

5143

82

Femalefou

nder

051

7050

0minus01

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

9001

50

007

000

24

Charita

bleg

ivingperc

apita

(log)

713

1060

1minus00

07minus00

640

392

5Co

mmercia

lnonprofits(lo

gCBS

A)

minus15

55015

5minus00

270

001minus03

70minus00

016

Governm

ent-fun

dedno

nprofits(log

CBS

A)

minus04

56012

0minus00

070

011minus00

960

232

037

77

Popu

latio

n(lo

gCBS

A)

151

61127

6minus00

43minus00

010

117

019

2minus00

920

164

8Incomep

ercapita

(log

CBS

A)

103

57016

30

026minus00

320

350

063

00

008

040

10

451

9Mem

bero

fateam

018

5038

90

039minus00

690

025

000

7minus00

52minus00

680

057

003

910

Localbeneficia

ries

052

2050

00

022

003

6minus00

180

006

000

10

006minus00

54minus00

410

058

11Workedin

for-p

rofit

organizatio

n0

142

034

9minus00

300

030

001

4minus00

04minus00

110

025

002

10

005minus00

300

006

12Degreeinbu

siness

010

1030

20

107minus00

170

005minus00

56minus00

17minus00

600

023minus00

34minus00

28minus00

320

059

13AfricanAmerica

n0

330

047

1minus00

730

074minus00

03minus00

38minus00

17minus00

530

056minus00

88minus00

72minus00

42minus00

050

091

14Femalefou

ndertimesFemaleb

usinesso

wners

(meancentered

)0

000

001

00

028

001

60

687

027

9minus02

72minus01

060

065

019

0minus00

170

014

012

5minus00

480

028

Note

n

584

Table 2 Mixed-Effects Ordinal Logistic RegressionsEstimating the Effect of Local Female Business Ownershipon the Commercialization of Nascent Social Ventures

1 2 3

Female founder minus0460lowastlowastlowast minus0471lowastlowastlowast(0164) (0167)

Female foundertimes 23910lowastlowastFemale business owners (9837)

Female business owners 1109 1654 minus8785(prop CBSA mean centered) (7359) (7241) (9013)

Charitable giving per minus0118 minus0166 minus0195capita (log) (0158) (0156) (0153)

Commercial nonprofits minus0827 minus0768 minus0746(log CBSA) (0723) (0698) (0688)

Government-funded 0881 0822 0855nonprofits (log CBSA) (1278) (1258) (1250)

Population (log CBSA) minus0097 minus0103lowast minus0107lowast(0063) (0061) (0061)

Income per capita (log CBSA) 0537 0613 0765(0691) (0625) (0637)

Member of a team 0109 0061 0083(0215) (0226) (0228)

Local beneficiaries 0040 0057 0042(0139) (0144) (0143)

Worked in for-profit organization minus0225 minus0202 minus0285(0283) (0283) (0287)

Degree in business 0822lowastlowast 0775lowastlowast 0830lowastlowast(0376) (0387) (0386)

African American minus0281lowast minus0265lowast minus0276lowast(0166) (0160) (0161)

Controls forYear Yes Yes YesEducational attainment Yes Yes YesProgram area of project Yes Yes Yes

Observations 584 584 584Number of CBSAs 104 104 104

Notes Robust standard errors clustered by CBSA are in parenthesesSignificance levels are based on two-tailed testslowastp lt 01 lowastlowastp lt 005 lowastlowastlowastp lt 001

their variance inflation factors all of whichwere signif-icantly less than 10 and had a mean of 146 indicatingno cause for concern (Belsley et al 1980)

ResultsTable 2 presents regression estimates in the same orderas the hypotheses Model 1 is a baseline model con-taining all control variables Model 2 tests Hypothe-sis 1 which posits that female social venture founderswill use commercial activity to a lesser degree thanmale social venture founders The coefficient for femalegender of founder is negative and statistically signif-icant in support of Hypothesis 1 We further esti-mated predicted probabilities for each level of com-mercialization by gender keeping all other covariatesat their means Predicted probabilities represent theestimated probability for a member of each gender touse each level of commercialization Figure 1 shows

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Figure 1 Predicted Probability of Using Each Level ofCommercialization in Social Venture by Founderrsquos Gender

0010203040506070809

1 2 3 4 5

Pre

dict

ed p

roba

bilit

y

Level of commercialization (1 = No commercialactivities 5 = Only commercial activities)

Female founders Male founders

Note Differences between genders are significant at the 005 levelwithin all levels of commercialization

these results which indicate statistically significant dif-ferences between genders within each level of com-mercialization According to these estimates the pre-dicted probability of commercialization is higher formen than for women at all levels of commercializationeven for the most minimal level of commercializationwhile the predicted probability of not using any com-mercial activity is higher for women than for men

Model 3 in Table 2 tests Hypothesis 2 which pre-dicts that the presence of female business owners inthe local community will weaken the effect of gen-der on the use of commercial activity The coefficienton the interaction between female founder and theproportion of female local business owners is positiveand statistically significant in support of Hypothesis 2Figure 2 plots predicted conditional probabilities forfemale founders at different levels of local female busi-ness ownership for each level of commercial activityThese analyses show a consistent positive relationshipbetween local female business ownership and the pre-dicted probability of commercialization at all positivevalues of commercial activity (levels 2 to 5) Simulta-neously increased local female business ownership isassociated with a decrease in the predicted probabil-ity that female founders use no commercial activity(level 1)

Finally examining the control variables throughoutthe models in Table 2 we observe that the control forhaving a degree in business was statistically significantand positive which is consistent with findings fromresearch on business education and entrepreneurship(Peterman and Kennedy 2003) Furthermore the indi-cator for being African American was marginally sig-nificant and negative indicating that AfricanAmericanapplicants were potentially less associated with com-mercialization The remaining control variables whichwere not statistically significant had signs in accor-dance with our theoretical framework

Robustness ChecksWe performed a number of tests to assess the robust-ness of the results In particular we used coarsenedexact matching (CEM Iacus et al 2011) on the charac-teristics of social venture founders and their projects toensure that our results were not sensitive to potentialimbalances in our sample All our results held underthis approach We also replicated our results exclud-ing social ventures that had not yet been launchedwhich helped ensure that our results were robust toheterogeneity in the maturity of social ventures in thesample Furthermore we replicated our results withadditional control variables to account for the potentialinfluence of local government spending economic con-ditions in the local community and the demographicsof the local community We also tested for the poten-tial effect of the presence of women in noncommercialleadership positions in the local community by includ-ing interactions of the social venture founderrsquos genderwith the presence of female congressional represen-tatives and the proportion of local nonprofit leaderswho were women and we found no evidence of aneffect Furthermore we replicated our results usingordinary least squares and ordinal probit models toensure that our results were robust to our estimationmethod Finally we used simulation techniques to esti-mate the behavior of social venture founders undercounterfactual community conditions which helpedtest whether our hypotheses hold under amore generalarray of conditions We refer the reader to the onlineappendix for detailed descriptions of these robustnesschecks

Constructive Replication Gender andCommercialization in Nonprofit EntrepreneurshipWe introduced a novel theoretical lensmdashgendermdashthroughwhich to understand the commercialization ofthe social sector In doing so we theorized that cul-tural beliefs about gender which present commercialactivity as more appropriate for men and less appro-priate for women will result in relatively less commer-cialization by female social venture founders but thatthe presence of women business owners in the localcommunity can weaken local cultural beliefs regardinggender and commercialization thus increasing com-mercial activity by female social venture founders

Our empirical analysis has some potential limita-tions First our sample of social venture founders maynot be fully representative of the population of socialventure founders because of self-selection into the fel-lowship competition we studied We addressed thisissue through numerous robustness checks includingthe use of CEM and simulations but are limited by ourdata Second our sample focuses on early stage ven-tures While this should alleviate concerns with sur-vivorship bias a common limitation in entrepreneur-ship research (Davidsson 2006) questions may remain

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Figure 2 (Color online) Predicted Probabilities of Using Each Level of Commercialization in a Social Venture by Proportionof Female Business Owners in Community and Founderrsquos Gender (Level 1No Commercial Activity 5Only CommercialActivity)

05

06

07

08

09

Pro

babi

lity

011 013 015 017 019 021

Female business owners (prop)

011 013 015 017 019 021


011 013 015 017 019 021


Level 1 Commercialization

003

004

005

006

Pro

babi

lity


004

005

006

007

008

009

Pro

babi

lity


011 013 015 017 019 021


011 013 015 017 019 021


004

006

008

010

012

Pro

babi

lity


005

010

015

020

Pro

babi

lity


Note Circles indicate male founders triangles indicate female founders

about the theoryrsquos relevance to fully operational ven-tures Finally the previous analyses do not explorean important and related question What happens tothe survival of social ventures that commercialize Inparticular is there an association between the genderof social venturesrsquo leaders and the venturesrsquo survivalwhen they use commercial activity

In response to these potential limitations we under-took a constructive replication in which we tested ourhypotheses using a different sample and different oper-ational definitions of our constructs not subject to thesame concerns as ourmain sampleWe tested ourmainhypotheses predicting the use of commercial activi-ties then conducted additional analysis regarding howa founderrsquos gender and the use of commercial activ-ities affect a social venturersquos survival Constructivereplications test the robustness of relationships acrossempirical methods and settings by testing hypothe-sized relationships among constructs while varyingtheir operationalization (Cicchetti and Grove 1991Hendrick 1990 Kelly et al 1979) Such multisampleconstructive replications have been used extensivelyin organizational behavior research (Downey et al

1979 Kemery et al 1985 McNatt and Judge 2004) Inour setting constructive replication helps address themethodological concerns of our prior sample regard-ing biased selection into our original sample whilealso testing the empirical and theoretical generalizabil-ity of the hypothesized relationships with regard tofully operational ventures and questions around ven-ture survival

To conduct a constructive replication we used a sec-ond data set on nonprofit entrepreneurship This dataset shares important characteristics with our originalsample of social ventures Specifically new nonprofitorganizations are similar to our social ventures in thatthey are recently founded are social sector organiza-tions devoted to a social mission and also face com-mercialization pressures These data capture the fullpopulation of newly founded nonprofit organizationsFurthermore the data set has the longitudinal struc-ture required to test for venture survival We beganby replicating our main analyses with this data setand then proceeded to a supplemental analysis of howorganizational survival was associated with femaleleadership and use of commercial activity

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Our primary source for the supplemental datawas the NCCS-GuideStar National Nonprofit ResearchDatabase (2008) produced by the National Centerfor Charitable Statistics at the Urban Institute Thisunique one-year project captured detailed informa-tion about the full population of nonprofit organiza-tions in the United States during 2003 largely basedon data extracted from tax filings for that year (Inter-nal Revenue Service Form 990) To be consistent withour initial analysis which focused on ventures in exis-tence for less than two years we limited our sample toventures founded during 2001 2002 and 2003 a totalof 32940 nonprofit ventures While we could identifyfounders in the data we also had information on othermembers of top leadership who were likely to havesignificant influence on decisions to use commercialactivity Thus we extended our analyses from femalefounder to include female leadership To identify thegender composition of leadership in these organiza-tions we used the names of the top five ranking officersof each organization along with their titles as listed intheir Form 990 filed with the Internal Revenue ServiceWe treated officers with the title of ldquofounderrdquo ldquoexecu-tive directorrdquo or ldquochief executive officerrdquo as the leadersof the organization A binary variable for female leadertook the value 1 if a woman occupied at least one ofthese leadership titles Less than 2 of organizationsin the sample had more than one individual with oneof these leadership titlesTo identify each leaderrsquos gender we matched each

first name to statistics on the use of that name by eachgender in the US population (US Census Bureau1995 Social Security Administration 2016) Using thisapproach we were able to identify the gender of offi-cers from 31160 nonprofits (946 of sample) Thisinvolved assigning a gender to a total of 222227 firstnames that appeared in the data We obtained statis-tics on the use of names by gender from the 1990data set ldquoFrequently Occurring Surnames from Cen-sus 1990rdquo (US Census Bureau 1995) which is basedon a national sample of 1990 census records stratifiedby race gender and geography We supplemented thenames obtained from this source with names occurringin the Social Security national data set of given names(Social Security Administration 2016) Our approachyielded matches for 205715 first names (925 ofnames) A small number of observations for leadershad missing names (968 observations) Moreover wewere unable to assign a gender to certain gender-ambiguous names such as Jamey Leslie and SydneyFollowing prior research (Kalnins and Williams 2014)we assigned a gender to a name if 95 or more ofoccurrences in the census and Social Security Admin-istration data were associated with that gender Thisled to the exclusion of 1321 observations for individ-ual leaders We also ran all analyses with a cutoff of

60 for assigning gender to a name and all resultsheld unchanged Finally we left 14223 first names(64 of the sample) unmatched primarily becausenames appeared either as abbreviated nicknames orinitials

To measure the use of commercial activity we reliedon additional financial information from tax filingsfor each year from 2003 to 2007 Nonprofit account-ing divides revenues into program services and duesreceived in exchange for the provision of programsand those from public and charitable donations Fol-lowing prior studies of nonprofits we measured com-mercialization as the percentage of total revenues fromprogram revenues and dues (Galaskiewicz et al 2006)Consistent with our main analysis we measured theproportion of female business owners in the local com-munity using the US Survey of Business Owners Forthe replication analyses we used the 2002 edition ofthe survey which was closest to the date of the non-profit leadership data for 2003 For our survival anal-yses covering 2003 to 2007 we used both the 2002 and2007 editions of the survey and imputed values forthe proportion of female business owners during 2004to 2006 using linear interpolation (Little and Rubin1987) We further supplemented these data with otherorganization-level control variables using the Form990 tax filings for each organization In particular weincluded a control for the presence of female officers inthe nonprofit This binary variable took the value of ldquo1rdquoif at least one of the non-leader officers was female andldquo0rdquo if all officers listedweremenWe also included con-trols for the total assets of the organization (logged tocorrect for skewed distribution) and the age of the orga-nization estimated as the number of years since theorganization obtained nonprofit status We also con-trolled for possible influence of government fundingon commercialization by including a binary indicatorof whether the nonprofit organization received govern-ment support In addition to these controls the regres-sions included fixed effects for the nonprofitrsquos servicecategory taken from theNational Taxonomy of ExemptEntities (NTEE) This code assigns an ldquoindustryrdquo clas-sification similar to Standard Industrial Classificationcodes for for-profit businesses Moreover we includedcommunity-level controls similar to those in our mainanalyses of social ventures Specifically we controlledfor the amount of charitable giving per capita in thelocal communitymeasured as the sumdonated to pub-lic charities in the nonprofitrsquos CBSA divided by thepopulationWe also controlled for the logged nonprofitorganization population in each CBSA measured asthe total number of public charities that filed Form 990with the IRS during a year To account for competitivepressures from other nonprofit organizations we con-trolled for the niche size measured as the proportionof local nonprofits in the same NTEE category as the

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eser

ved


focal nonprofit Finally we controlled for income percapita in the corresponding community-year obtainedfrom the Bureau of Economic Activity Regional Eco-nomic Accounts data series The resulting data set wasa panel of newly founded nonprofits covering 2003 to2007 including for each its level of commercializationthe gender of its leader other organizational character-istics and characteristics of the community in whichit is located Table 3 presents descriptive statistics forthese variablesTo begin our constructive replication we repeated

the regression analyses from Table 2 We estimatedthe models using a multilevel mixed effects modelspecified in the same manner as Table 2 modified toaccount for our continuous measure of commercial-ization Table 4 presents the results Model 1 presentsthe control variables Model 2 introduces the gen-der of the nonprofit leader Consistent with Hypothe-sis 1 and our main analysis the female gender of theleader is statistically significant and negatively associ-ated with commercialization Model 3 introduces theinteraction with the proportion of local business own-ers who are women The interaction is positive and sta-tistically significant consistent with Hypothesis 2 andour main analysis Thus our main results are repli-cated in this new sample providing further supportfor our theoretical arguments While nonprofit orga-nizations are a narrower sampling frame than socialventures they share the core features of our theorylike social ventures at large recently founded non-profit organizations pursue a social mission operatein a feminine-typed sphere and display increasingcommercialization The consistency of these findingswith our main analysis thus lends greater confidencein those results

Having established this constructive replication wefurther examined the survival of these ventures overthe period 2003 to 2007 In our sample 7807 failureswere recorded during this period Table 5 presentsour results Because our observations of survival areannual we chose a discrete time survival model thecomplementary logndashlog model Model 1 of Table 5presents the control variables Model 2 introduces anindicator for whether the nonprofitrsquos leader is femalewhich produces a nonsignificant estimate that sug-gests no effect of leaderrsquos gender on survival NotablyModel 3 indicates no effect of commercialization onsurvival Finally Model 4 includes the interaction offemale founder and commercial revenue and finds apositive and statistically significant estimate for thisinteraction which indicates that the likelihood of fail-ure in any given year increases when women-led non-profits use commercial means more extensively Takentogether these findings indicate that while leaderrsquosgender and venture commercialization independentlyhave no statistically discernible effect on survival Table3

SummaryStatistic

sfor

Sampleof

Non

profi

tOrgan

izations

Mean

SD

12

34

56

78

910

11

1Co

mmercia

lrevenue

(prop)

028

80

889

2Femaleleader

010

50

307

minus00

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

90

019

minus00

030

012

4Femaleo

fficers

presentinno

nprofit

056

90

495

minus00

020

209

minus00

045

Assets(log)

111

312

182

001

70

036

minus00

160

036

6Age

253

11

176

000

70

033

000

30

038

011

97

Governm

entsup

port

000

60

076

minus00

060

009

minus00

010

022

000

80

029

8Ch

arita

bleg

ivingperc

apita

(log

CBS

A)

245

34268

10minus00

060

014

012

2minus00

130

027

minus00

130

001

9Nonprofitp

opulation(lo

gCBS

A)

555

31

448

minus00

060

002

038

7minus00

460

007

minus00

13minus00

110

312

10Nonprofitn

iche

010

00

070

002

5minus00

14minus00

690

073

minus00

30minus00

08minus00

05minus00

53minus01

8411

Incomep

ercapita

(log

CBS

A)

104

550

176

minus00

080

018

034

7minus00

080

020

minus00

15minus00

140

372

073

1minus01

4312

Femaleleadertimes

Femaleb

usinesso

wners

(meancentered

)0

000

000

60

003

003

10

330

000

60

000

000

6minus00

010

052

013

2minus00

340

127

Note

n

311

60

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nloa

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from

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128

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149

52]

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2017

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Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved


Table 4 Mixed-Effects Regressions Estimating the Effect ofLocal Female Business Ownership on theCommercialization of New Nonprofit Organizations 2003

1 2 3

Female leader minus0042lowastlowastlowast minus0042lowastlowastlowast(0008) (0007)

Female leadertimesFemale 0820lowastlowastbusiness owners (0372)

Female business owners 0156 0162 0075(prop CBSA mean centered) (0261) (0261) (0276)

Female officers present minus0019 minus0014 minus0014in nonprofit (0013) (0013) (0013)

Assets (log) 0007 0007 0007(0005) (0005) (0005)

Age 0003 0004 0004(0004) (00035) (0004)

Government support minus0063lowastlowast minus0062lowastlowast minus0062lowastlowast(0025) (0025) (0026)

Charitable giving per 0001 0001 0001capita (log CBSA) (0001) (0001) (0001)

Nonprofit population (log CBSA) 0003 0003 0003(0005) (0005) (0005)

Nonprofit niche 0010 0013 0015(0073) (0073) (0073)

Income per capita minus0051 minus0049 minus0050(log CBSA) (0032) (0032) (0032)

NTEE fixed effects Yes Yes YesConstant 0445 0423 0430

(0321) (0322) (0322)Observations 31160 31160 31160Number of CBSAs 355 355 355

Notes Robust standard errors are in parentheses clustered at theCBSA level Significance levels are based on two-tailed testslowastlowastp lt 005 lowastlowastlowastp lt 001

female-led ventures are significantly less likely to sur-vive than male-led ventures at higher levels of com-mercialization These results extend our main analysisby providing some initial evidence of important orga-nizational consequences to the incorporation of com-mercial activities by female social venture foundersThese survival results are interesting to consider

from the perspective of our theory Previous researchsuggests that female entrepreneurs on average pos-sess lower levels of human and social capital requiredto survive (Kalleberg and Leicht 1991 Loscocco et al1991) yet we find no statistical evidence that female-led organizations are less likely to survive nor thatcommercialization is a detriment to survival despitebeing at odds with the charitable norms of the socialsector Our findings do suggest however that survivalis negatively associated with female-led ventures thatcommercialize in which these factors appear togetherFuture research should further investigate these resultsregarding survival however as our data cannot con-clusively differentiate whether the lower likelihood of

survival is a result of backlash for violating gender andsectoral norms or a result of womenrsquos lower levels ofhuman and social capital with regard to commercialactivity in the social sector

The relatively lower rate of survival of female-ledsocial ventures at higher levels of commercializationsuggests that women who found commercial venturesmay not be fully aware of the challenges they will faceor are influenced in their choice to commercialize byfactors beyond organizational survival While we can-not observe directly in our data the specific causes ofeach organizationrsquos survival or failure our theoreti-cal approach offers a number of interesting paths forfuture research on this issue For instance previousstudies indicate that entrepreneurs develop expecta-tions of their success in part by observing the experi-ences of other founders and ventures that they perceiveas similar to them (Bosma et al 2012) Female foundersof commercial social ventures have relatively fewmod-els for behavior which may lead to expectations thatsystematically underestimate the degree of backlashthat they will face

This finding may also be explained by conflictingcultural beliefs about gender in the entrepreneurrsquosenvironment For instance while the presence offemale business owners in a local community mayweaken the sex typing of commercial activity suffi-ciently to make it more amenable to female social ven-ture founders it may not alter the level of backlashfemale social venture founders may face when theydo commercialize Indeed from our data it is unclearto what extent the presence of female business own-ers influences these intermediate factors such as back-lash and social capital that affect the survival of socialventures

Overall these supplemental analyses build on ourmain analyses to suggest that community gendernorms may enable female social venture founders toengage in commercial activity but that the choice tocommercialize may threaten the survival of female-ledorganizations

DiscussionOur paper examines the critical but overlooked roleof cultural beliefs about gender in understanding hownewly formed organizations in the social sector inte-grate commercial activity Our results first suggestthat congruence between the gender of social ven-ture founders and commercial activity is an importantpredictor of commercialization female social venturefounders are less likely to use commercial activity thantheir male counterparts due to cultural beliefs that dis-associate women from commercial activity They alsosuggest however that cultural beliefs about genderand commercial activity in the local community alsomatter the presence of female business owners in the

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Table 5 Discrete Time Survival Model of Nonprofit Organizations 2003ndash2007

1 2 3 4

Female leader minus0033 minus0078lowastlowast(0033) (0037)

Commercial revenue minus0073lowast minus0141lowastlowastlowast(0041) (0051)

Female leadertimesCommercial revenue 0174lowastlowast(0082)

Female business owners (prop CBSA mean centered) 2690lowastlowastlowast 2716lowastlowastlowast 2695lowastlowastlowast 2716lowastlowastlowast(0921) (0921) (0921) (0920)

Female officers present in nonprofit minus0080lowastlowast minus0070lowastlowast minus0081lowastlowast minus0069lowastlowast(0033) (0034) (0033) (0034)

Assets (log) minus0180lowastlowastlowast minus0180lowastlowastlowast minus0180lowastlowastlowast minus0180lowastlowastlowast(0007) (0007) (0007) (0007)

Age minus0139lowastlowastlowast minus0139lowastlowastlowast minus0139lowastlowastlowast minus0139lowastlowastlowast(0013) (0013) (0013) (0013)

Government support minus0269 minus0269 minus0273 minus0272(0172) (0172) (0171) (0171)

Charitable giving per capita (log CBSA) minus0001 minus0001 minus0001 minus0001(0001) (0001) (0001) (0001)

Nonprofit population (log CBSA) minus0006 minus0007 minus0007 minus0007(0015) (0015) (0015) (0015)

Nonprofit niche minus1147lowast minus1156lowast minus1135lowast minus1143lowast(0633) (0633) (0632) (0633)

Income per capita (log CBSA) 352eminus07 426eminus07 289eminus07 344eminus07(267eminus06) (267eminus06) (267eminus06) (267eminus06)

Time 1689lowastlowastlowast 1688lowastlowastlowast 1689lowastlowastlowast 1688lowastlowastlowast(0057) (0057) (0057) (0057)

Time squared minus0189lowastlowastlowast minus0189lowastlowastlowast minus0189lowastlowastlowast minus0189lowastlowastlowast(0008) (0008) (0008) (0008)

NTEE fixed effects Yes Yes Yes YesObservations 132212 132212 132212 132212

Notes The dependent variable is the risk of failure in any given year Positive coefficients indicate a higher likelihood of failure Robuststandard errors are in parentheses clustered by nonprofit organization Significance levels are based on two-tailed testslowastp lt 01 lowastlowastp lt 005 lowastlowastlowastp lt 001

same community mitigates the role of foundersrsquo gen-der on the use of commercial activity By highlightinghow gendered aspects of both the social and commer-cial sector interact to shape the use of commercial activ-ity by social venture founders our findings contributeto research on hybrid organizations in the social sectorcommunities as a context for the enactment of genderand the enactment of gender in entrepreneurship

Creation of Hybrid OrganizationsOur study contributes to research on hybrid orga-nizations that combine aspects of multiple organiza-tional forms (Battilana et al 2015 Haveman and Rao2006 Padgett and Powell 2012) such as social ven-tures that primarily pursue a social mission but engagein commercial activity to sustain their operations(Battilana and Lee 2014 Galaskiewicz and Barringer2012 Tracey et al 2011) Previous research on thesehybrids has focused on examining the organizationalconsequences of hybridity (Battilana and Dorado 2010Pache and Santos 2013) but has paid scant attention to

the antecedents of hybridity (Battilana and Lee 2014Tracey et al 2011) The antecedents of hybrid orga-nizations present a puzzle for organizational theoryas hybrid organizations do not follow well-definedorganizational archetypes to which new ventures faceinstitutional pressures to conform (Aldrich and Fiol1994) Prior theorizing has focused on field-level pro-cesses that lead to the founding of hybrid organizations(Haveman and Rao 2006) but less attention has beenpaid to the role of individual founders (Powell andSandholtz 2012)

Our study complements the above research by show-ing how cultural beliefs regarding the appropriatenessof commercial activity by women influence hybridiza-tion and thus provides an initial investigation into theintersection between hybrid organizations and issuesof culture and gender Recent institutional researchhas emphasized the plurality of social pressures andtheir simultaneity in determining social outcomes yethas largely viewed these pressures and their outcomesas undifferentiated at the individual level nor does

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it systematically account for differences in how insti-tutional pressures might affect individuals depend-ing on their characteristics (Hallett 2010 Reay et al2006) Research on gender by contrast accounts fordifferences in how cultural beliefs affect individualsrsquobehaviors (Ridgeway and Correll 2004) Gendered cul-tural beliefs tend to amplify menrsquos responses to pres-sures to use commercial sources of funding whileinhibiting similar responses bywomenWe believe thatthis insight is important for scholars of hybridizationand of institutional change more generally field-levelchanges depend not only on field-level dynamics butalso on the actions of many individual participants andtheir constraining or enabling social roles (Rao et al2005) This finding may have further implications forinstitutional change and its outcomes For instance webelieve that future research should examine whethercommercialization changes the long-term sex-typingof the social sector as well as whether similar dynam-ics influence change in other gendered industries andorganizational fields

Local Communities and the Enactment of GenderOur study alsomakes important contributions to schol-arship on gender in organizations particularly fromthe standpoint of the interaction between local com-munities and social venture founders Contemporaryscholarship on gender in organizations has shown thatgender is situationally enacted (Martin 2004 Ridgeway2011) yet it has overlooked a fundamentally impor-tant social relational context for gender enactment thelocal community We find that the effect of a social ven-ture founderrsquos gender on the use of commercial activ-ity depends upon the gendered characteristics of thelocal community in which the founder is embeddedWe argue that community-level differences in culturalbeliefs are critical for understanding whether men andwomen enact gendered norms in their social venturesOur findings regarding female business owners can

be viewed in light of recent research showing howchanges in political power structures in local commu-nities influence the empowerment of female commu-nity members In a field study in India Beaman et al(2012) showed that a policy that prescribed greater rep-resentation of women on village councils eliminateddeficits in adolescent girlsrsquo educational attainment andincreased household gender equity in those villagesIn organizational research emerging work broadlysuggests that geographically based gender norms canshape organizational outcomes such as founding sur-vival and performance (Kalnins and Williams 2014Post and Byron 2015 Theacutebaud 2015) Our findings fur-ther suggest that geographic community-level effectsmay extend to local cultural beliefs regarding genderand commercial activity Our work contributes to these

new lines of inquiry by closely examining community-level gender norms and the very activities in whichorganizations engage

Taking into account local variations in culturalbeliefs about gender also contributes to research onthe influences of geographic communities on organi-zational patterns (Davis and Marquis 2005) Studiesin this area have brought attention to the various ele-ments of communities that affect organizational activ-ities For example studies have shown that commu-nity networks and traditions affect corporate socialresponsibility practices (Marquis et al 2007 Tilcsik andMarquis 2013) and investment strategies (Lounsbury2007) Our study adds to this literature by consider-ing how aspects of the local community influence theenactment of gender in emergent organizations More-over by considering cross-level interactions betweenthe community and individuals we offer a multilevelperspective on the effects of communities on the found-ing and development of organizations (Marquis andBattilana 2009)

The Enactment of Gender in the Social andBusiness SectorsFurthermore our study is unique in highlighting howthe presence of women in the business sector mayshape the gender enactment of women in the social sec-tor within a local community Our empirical demon-stration of the role of female business owners in alocal community extends theoretical work that sug-gests female business owners are uniquely located atthe nexus of family community and business (Brush1992) and shows how they may be important con-duits between the business and social sectors In doingso we bring together gender research that has exam-ined women in male-dominated settings (Ely 1995Kanter 1977) such as women in the business sectorwith gender research on female-dominated settings(Williams 1992) such as the social sector The for-mer has highlighted how an increasing proportion ofwomen within a single male-dominated organizationor industry can alter womenrsquos self-assessments andbehavior within that organization or industry (Ghaniet al 2014 Ely 1995) while the latter has largely high-lighted the advantages that men gain when enteringfemale-typed contexts (Williams 1992) Yet one way ofunderstanding our finding is that women who disruptgender norms in one sector (as business owners) canaffect women disrupting gender norms in another (associal venture founders) Future research should exam-ine the possible mechanisms underlying such cross-sectoral influences within local communities in greaterdetail Future research may also examine how othergendered characteristics of communities affect com-mercial activity

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In addition our study has implications for themean-ing of commercial activity in the social sector a pre-dominantly feminine occupational setting Indeed ourfindings can be viewed in different ways depending ononersquos normative position regarding commercial activ-ity in the social sector For instance one speculationarising from our finding is that commercialization ofthe social sector may be seen as a process of masculin-ization and that women are disadvantaged despitebeing a demographic majority in the sector An alter-native possibility is that women may be resisting mas-culinization and defending the female-typed work ofthe sector because they are the demographic majorityin the sector How the lack of commercialization byfemale social venture founders can be both a perpet-uation of gender inequality and a form of resistanceto masculinization and commercialization is an issueworthy of future investigation

Gender and EntrepreneurshipOur study contributes to research on womenrsquos entre-preneurship by examining the gendered nature oforganizational activity at the time of founding Whileprevious research has identified gender differencesbetween entrepreneurs in terms of founding rates(Bowen and Hisrich 1986 Jennings and Brush 2013)performance (see eg Robb and Watson 2012) anddiscrimination (Gupta and Bhawe 2007 Kacperczyk2013 Yang and Aldrich 2014) relatively little researchhas examined differences in the specific activities usedby women and men starting new ventures (for anexception see Cliff et al 2005) Our study furthersthis research by examining the extent to which womensocial venture entrepreneurs use commercial activityIn doing so we show how the behavior of individ-ual entrepreneurs is contingent both on cultural beliefsregarding gender and the prevalence of those beliefs inlocal communities

These findings draw attention to the importance ofentrepreneurship as a mechanism for the transmissionand persistence of cultural beliefs regarding the appro-priate vocational activities of women (Brooks et al2014 Phillips 2005) Our study builds on previousresearch by showing how gendered cultural beliefs canalso lead to systematic differences in the organizationalmodels adopted by male and female founders Thisfinding converges with arguments that in the absenceof established rational or bureaucratic processes suchas those that might exist in established organizationscultural beliefs about gender are more likely to havea pronounced effect on individualsrsquo organizationalchoices as individuals rely on cultural beliefs to guideorganizational decisionmaking (Ridgeway 2011 2013)

Our study also responds to calls for research ongender and entrepreneurship in the social sector(Jennings and Brush 2013) Previous studies have typi-cally addressed this question by testing the adoption of

social goals by traditional entrepreneurs showing thatalthough women are less likely than men to engagein entrepreneurship women entrepreneurs are morelikely than men to emphasize social goals (Carter andAllen 1997) and to start social ventures (Harding 2006Hechavarria et al 2012 Sharir and Lerner 2006) Ourstudy views this question from the perspective of ven-tures started explicitly with a social goal and examinesvariation in the use of commercial activity In doingso our study contributes to the growing literatureon social entrepreneurship (Battilana and Lee 2014)Indeed it is the first study we are aware of that showsthe effect of community context on the relationshipbetween gender and social entrepreneurship

Limitations and Future DirectionsOur study has several limitations First our archivalsamples limit us from strictly ruling out the influenceof omitted variables and precisely identifying causalrelationships and mechanisms To address this lim-itation to the extent possible we included substan-tial control variables we collected data from severaldifferent sources mitigating concerns about commonmethod variance and we conducted a constructivereplication using longitudinal data and found con-vergent results across the two samples As McGrath(1981) notes gaining convergence with the use of mul-tiple studies in which each approach compensates forthe vulnerabilities of the other provides greater confi-dence in our results However future research couldbuild on our work by utilizing alternative methodolog-ical approaches For instance by leveraging qualitativemethodologies future studies can explore gender andcommercialization at a more fine-grained level exam-ining how gender affects foundersrsquo subjective percep-tions and understandings of the social sector and com-mercial activity within local communities

Second our theoretical framework proposed that thepresence of female business owners alters the specificbeliefs disassociating women from commercial activ-ity rather than more general gendered cultural beliefsregarding both women and men in a variety of waysFuture studies might consider how local communitiesaffect cultural beliefs thatmay influencemale foundersrsquoorganizational choices Results from our first sampleof social venture founders suggest that as the propor-tion of female business owners in the local communityincreases men become more likely to use noncom-mercial revenue models as evidenced in the predictedprobabilities for men using commercial activities (seeFigure 2) This may be because as the proportion offemale business owners increases in the local commu-nity male founders may be less constrained as com-mercial activity is not as clearly masculine typed andthus less clearly associatedwith enacting gender How-ever further research is needed to determine whether

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this is the case since the evidence in our data is toolimited to confirm itThird given research on the rise of commercial-

ization and hybridization we built theory about theuse of commercial activity in new ventures as animportant dependent variable in its own right How-ever the results of our supplemental analyses revealthat female-led new ventures that commercialize areless likely to survive Future research should furtherinvestigate this relationship and identify the factorsthat decrease survival for female-led nonprofits thatcommercialize It should also examine other relateddependent variables such as the social and economicperformance of these social ventures as well as otheraspects of community-level gendered cultural beliefs

Fourth our data did not reveal significant teamdynamics yet existing research on entrepreneurshipindicates that teams and groups play an importantrole at the time of founding for traditional enterprises(Ruef 2010) and social enterprises as well as specifi-cally in relation to gender in founding teams (Yang andAldrich 2014) Although team dynamics were not a keyfactor in the two samples studied here future researchmay explore gendered dynamics in founding teams bycollecting additional data at that level of analysis

Last our study is situated in the US social sectorand our findings should be interpretedwithin this con-text Their implications for other contexts will dependon the extent to which these other contexts share simi-lar cultural beliefs about the gender appropriateness ofcommercial activity as well as the general acceptabilityof commercial activity in social ventures Future workmay wish to examine these dynamics in a comparativeperspective either extending the work to other sectorsin the United States (including the corporate and pub-lic sectors) or to social venture founders in countriesthat have different cultural beliefs about gender andordifferent patterns of organizing in the social sector

ConclusionThe commercialization of the social sector over the past30 years breaks from traditional sectoral boundariesby blending commercial and social activity within asingle organization This sectoral transformation chal-lenges other social structures such as cultural beliefsregarding gender and the appropriateness of commer-cial work Our study sheds new light on this processby examining it through the lens of gender as sociallyconstructed and locally situated (Martin 2004 Ridge-way 2013) In doing so we highlight the role of cul-tural beliefs about gender in the creation of hybridorganizations that pursue a social mission and engagein commercial activities to sustain their operationsImportantly we find that gendered aspects of both thesocial and business sectors play key roles in shapingthis trend While cultural beliefs about gender may

result in female social venture founders being lesslikely to use commercial activity than their male coun-terparts female business owners in local communitiesalso help to mitigate the effect of foundersrsquo gender onthe commercialization of social ventures by mitigat-ing cultural beliefs disassociating women from com-mercial activity Identification of these patterns bringsgender in local communities into focus as an impor-tant context for scholars of hybrid organizing genderand entrepreneurship We hope our study will cat-alyze further research on the intersection of gender andorganizational processes as well as the challenges andopportunities it presents for individuals and society

AcknowledgmentsThe authors would like to thank senior editor Sarah Kaplanand three anonymous reviewers for their valuable com-ments on earlier versions of this work They also wishto acknowledge the helpful comments received from ErinReid and Metin Sengul They are grateful to participants inthe Harvard Business School Organizational Behavior work-shop 2015 the 2015 Academy of Management Embedded-ness and Community Symposium the Harvard KennedySchoolrsquos 2016 Women and Public Policy Seminar the 2016Wharton People and Organizations Conference and the 2016Economic Sociology Conference They also thank MarissaKimsey Christy Ley Jean Sohn and Ting Wang for excellentresearch assistance

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Battilana J Sengul M Pache AC Model J (2015) Harnessing produc-tive tensions in hybrid organizations The case of work integra-tion social enterprises Acad Management J 58(6)1658ndash1685

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Correll SJ (2004) Constraints into preferences Gender status andemerging career aspirations Amer Sociol Rev 69(1)93ndash113

CuddyAJ Fiske ST Glick P (2004)When professionals becomemoth-ers warmth doesnrsquot cut the ice J Soc Issues 60(4)701ndash718

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Eagly AH Karau SJ (2002) Role congruity theory of prejudice towardfemale leaders Psych Rev 109(3)573ndash598

Eagly AH Steffen VJ (1984) Gender stereotypes stem from the dis-tribution of women and men into social roles J Personality SocPsych 46(4)735ndash754

Eden D (2002) Replication meta-analysis scientific progress andAMJrsquos publication policy Acad Management J 45(4)841ndash826

Eikenberry AM Kluver JD (2004) The marketization of the nonprofitsector Civil society at risk Public Admin Rev 64(2)132ndash140

Ely RJ (1995) The power in demography Womenrsquos social construc-tions of gender identity at work Acad Management J 38(3)589ndash634

Ely R Padavic I (2007) A feminist analysis of organizational researchon sex differences Acad Management Rev 32(4)1121ndash1143

England P (2006) Toward gender equality Progress and bottlenecksBlau FD Brinton MC Grusky DB eds The Declining Significanceof Gender (Russell Sage Foundation New York) 245ndash264

Fantasia R Hirsch EL (1995) Culture in rebellion The appropria-tion and transformation of the veil in the Algerian revolutionJohnston H Klandermans B eds Social Movements and Culture(University of Minnesota Press Minneapolis) 144ndash159

Fauchart E Gruber M (2011) Darwinians communitarians and mis-sionaries The role of founder identity in entrepreneurshipAcad Management J 54(5)935ndash957

Foster W Bradach J (2005) Should nonprofits seek profits HarvardBus Rev 83(2)92ndash100

Frumkin P (2002) On Being Nonprofit A Conceptual and Policy Primer(Harvard University Press Cambridge MA)

Galaskiewicz J Barringer SN (2012) Social enterprises and social cat-egories Gidron B Hasenfeld Y eds Social Enterprises An Orga-nizational Perspective (Palgrave Macmillan New York) 47ndash70

Galaskiewicz J Burt RS (1991) Interorganization contagion in corpo-rate philanthropy Admin Sci Quart 36(1)88ndash105

Galaskiewicz J BielefeldWDowellM (2006)Networks and organiza-tional growth A study of community based nonprofits AdminSci Quart 51(3)337ndash380

Ghani E Kerr WR OrsquoConnell SD (2014) Political reservations andwomenrsquos entrepreneurship in India J Development Econom108(1)138ndash153

Greene PG Brush CG Hart MM Saparito P (2001) Patterns of ven-ture capital funding Is gender a factor Venture Capital 3(1)63ndash83

Grimes M (2010) Strategic sensemaking within funding relation-ships The effects of performance measurement on organiza-tional identity in the social sector Entrepreneurship Theory Prac-tice 34(4)763ndash783

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Groslashnbjerg KA Paarlberg L (2001) Community variations in the sizeand scope of the nonprofit sector Theory and preliminary find-ings Nonprofit Voluntary Sector Quart 30(4)684ndash706

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Hall PD (2006) A historical overview of philanthropy voluntary asso-ciations and nonprofit organizations in the United States 1600ndash2000 Steinberg R ed The Nonprofit Sector A Research Handbook(Yale University Press New Haven CT) 32ndash65

Hallett T (2010) The myth incarnate Amer Sociol Rev 75(1)52ndash74Halpern RP (2006)Workforce Issues in the Nonprofit Sector Generational

Leadership Change and Diversity (American Humanics KansasCity MO)

Hansmann H (1980) The role of nonndashprofit enterprise Yale Law J89(5)835ndash901

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Haveman HA Beresford LS (2012) If yoursquore so smart why arenrsquotyou the boss Explaining the persistent vertical gender gap inmanagement Ann Amer Acad Political Soc Sci 639(1)114ndash130

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Haveman H Rao H (2006) Hybrid forms and the evolution of thriftsAmer Behavioral Sci 49(7)974ndash986

Hechavarria DM Ingram A Justo R Terjesen S (2012) Are womenmore likely to pursue social and environmental entrepreneur-ship Hughes KD Jennings JE edsGlobal Womenrsquos Entrepreneur-ship Research Diverse Settings Questions and Approaches (EdwardElgar Publishing Ltd Cheltenham UK) 135ndash151

Heilman ME Block CJ Martell RF Simon MC (1989) Has anythingchanged Current characterizations of men women and man-agers J Appl Psych 74(6)935ndash942

Hendrick C (1990) Replications strict replications and concep-tual replications Are they important J Soc Behav Personality5(4)41ndash49

Hochschild AR Machung A (1989) The Second Shift Working Parentsand the Revolution at Home (Viking Press New York)

Hwang H Powell WW (2009) The rationalization of charity Theinfluences of professionalism in the nonprofit sector Admin SciQuart 54(2)268ndash298

Iacus SM King G Porro G (2011) Multivariate matching methodsthat are monotonic imbalance bounding J Amer Statist Assoc106(493)345ndash361

Irvine L Vermilya JR (2010) Gender work in a feminized professionThe case of veterinary medicine Gender Soc 24(1)56ndash82

Jay J (2013) Navigating paradox as a mechanism of change andinnovation in hybrid organizations Acad Management J 56(1)137ndash159

Jennings JE Brush C (2013) Research onwomen entrepreneurs Chal-lenges to (and from) the broader entrepreneurship literatureAcad Management Ann 7(1)663ndash715

Kacperczyk AJ (2013) Social influence and entrepreneurship Theeffect of university peers on entrepreneurial entry Organ Sci24(3)664ndash683

Kalleberg AL Leicht KT (1991) Gender and organizational perfor-mance Determinants of small business survival and successAcad Management J 34(1)136ndash161

Kalnins A Williams M (2014) When do female-owned businessesout-survivemale-owned businesses A disaggregated approachby industry and geograph J Business Venturing 29(6)822ndash835

Kanter RM (1977) Men and Women of the Corporation (Basic BooksNew York)

Kaplan S Vanderbrug J (2014) The rise of gender capitalism StanfordSoc Innovation Rev 12(3)36ndash41

Katz J Gartner WB (1988) Properties of emerging organizationsAcad Management Rev 13(3)429ndash441

Kellogg KC (2009) Operating room Relational spaces and microin-stitutional change in surgery Amer J Sociol 115(3)657ndash711

Kelly CW Chase LJ Tucker RK (1979) Replication in experimen-tal communication research An analysis Human Comm Res5(4)338ndash342

Kemery ER Bedeian AG Mossholder KW Touliatos J (1985) Out-comes of role stress A multisample constructive replicationAcad Management J 28(2)363ndash375

Kerlin JA (2006) Social enterprise in the United States and EuropeUnderstanding and learning from the differences Voluntas17(3)246ndash62

Kerlin JA Pollack TH (2011) Nonprofit commercial revenue Areplacement for declining government grants and private con-tributions Amer Rev Public Admin 41(6)686ndash704

Kirkham LM Loft A (1993) Gender and the construction of the pro-fessional accountant Accounting Organ Soc 18(6)507ndash558

Landis JR Koch GG (1977) The measurement of observer agreementfor categorical data Biometrics 33(1)159ndash174

Larsson R (1993) Case survey methodology Quantitative analy-sis of patterns across case studies Acad Management J 36(6)1515ndash1546

Light P (2008) The Search for Social Entrepreneurship (Brookings Insti-tution Washington DC)

Little RJA Rubin DB (1987) Statistical Analysis with Missing Data(Wiley New York)

Loscocco KA Robinson J Hall RH Allen JK (1991) Gender and smallbusiness success An inquiry into womenrsquos relative disadvan-tage Soc Forces 70(1)65ndash85

Lounsbury M (2007) A tale of two cities Competing logics and prac-tice variation in the professionalizing of mutual funds AcadManagement J 50(2)289ndash307

Lucas JW (2003) Status processes and the institutionalization ofwomen as leaders Amer Sociol Rev 68(3)464ndash480

Lykken DT (1968) Statistical significance in psychological researchPsych Bull 70(3)151ndash159

Marini MM Brinton MC (1984) Sex typing in occupational social-ization Reskin BF ed Sex Segregation in the Workplace TrendsExplanations Remedies (National Academy Press WashingtonDC) 192ndash232

Marlow S Patton D (2005) All credit to men Entrepreneurshipfinance and gender Entrepreneurship Theory Practice 29(6)717ndash735

Marquis C (2003) The pressure of the past Network imprinting inintercorporate communities Admin Sci Quart 48(4)655ndash689

Marquis C Battilana J (2009) Acting globally but thinking locallyThe enduring influence of local communities on organizationsRes Organ Behav 29(1)283ndash302

Marquis C LounsburyM (2007) Vive la reacutesistance Competing logicsand the consolidation of US community banking Acad Manage-ment J 50(4)799ndash820

Marquis C Davis GF Glynn MA (2013) Golfing alone Corpora-tions elites and nonprofit growth in 100 American communi-ties Organ Sci 23(5)1ndash19

Marquis C Glynn MA Davis GF (2007) Community isomor-phism and corporate social action Acad Management Rev 32(3)925ndash945

Martin CL Ruble D (2004) Childrenrsquos search for gender cues Cog-nitive perspectives on gender development Current DirectionsPsych Sci 13(2)67ndash70

Martin J (2000) Hidden gendered assumptions in mainstream orga-nizational theory and research J Management Inquiry 9(2)207ndash216

Martin PY (2004) Gender as social institution Soc Forces 82(4)1249ndash1273

McCarthy KD (2001) Women Philanthropy and Civil Society (IndianaUniversity Press Bloomington)

McGrath JE (1981) Dilemmatics The study of research choices anddilemmas Amer Behavioral Sci 25(2)179ndash210

McGregor J Tweed D (2002) Profiling a new generation of femalesmall business owners in New Zealand Networking mentoringand growth Gender Work Organ 9(4)420ndash438

McNatt DB Judge TA (2004) Boundary conditions of the Galateaeffect A field experiment and constructive replication AcadManagement J 47(4)550ndash565

Molotch H (1976) The city as a growth machine Toward a politicaleconomy of place Amer J Sociol 82(2)309ndash332

Moss TW Short JC Payne GT Lumpkin GT (2011) Dual identitiesin social ventures An exploratory study Entrepreneurship TheoryPractice 35(4)805ndash830

Odendahl T OrsquoNeill M (1994)Women and Power in the Nonprofit Sector(Jossey-Bass San Francisco)

Ott JS Dicke LA (2001) Challenges facing public sector manage-ment in an era of downsizing devolution dispersion andempowermentmdashAnd accountability Public Organ Rev 1(3)321ndash339

Pache AC Santos F (2013) Inside the hybrid organization Selectivecoupling as a response to competing institutional logics AcadManagement J 56(4)972ndash1001

Padgett JF Powell WW (2012) The Emergence of Organizations andMar-kets (Princeton University Press Princeton NJ)

Peterman NE Kennedy J (2003) Enterprise education Influencingstudentsrsquo perceptions of entrepreneurship Entrepreneurship The-ory Practice 28(2)129ndash144

Pfeffer J (1973) Size composition and function of hospital boards ofdirectors A study of organization-environment linkage AdminSci Quart 18(3)349ndash364

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from

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52]

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9 Se

ptem

ber

2017

at 1

109

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r pe

rson

al u

se o

nly

all

righ

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eser

ved


Phillips A (2005) Dilemmas of gender and culture The judge thedemocrat and the political activist EisenbergA Spinner-Halev Jeds Minorities within Minorities Equality Rights and Diversity(Cambridge University Press Cambridge UK) 113ndash134

Piore MJ Sabel CF (1984) The Second Industrial Divide Possibilities forProsperity (Basic Books New York)

Post C Byron K (2015) Women on boards and firm financial perfor-mance A meta-analysis Acad Management J 58(5)1546ndash1571

Powell WW Sandholtz KW (2012) Amphibious entrepreneurs andthe emergence of organizational forms Strategic Entrepreneur-ship J 6(2)94ndash115

Powell WW Steinberg R (2006) The Nonprofit Sector A Research Hand-book (Yale University Press New Haven CT)

Powell WW Gammal DL Simard C (2005) Close encountersThe circulation and reception of managerial practices in theSan Francisco Bay area nonprofit community Czarniawska-Joerges B Sevoacuten G eds Global Ideas How Ideas Objects andPractices Travel in a Global Economy (CBS Press Copenhagen)233ndash258

Putnam RD (2000) Bowling Alone The Collapse and Revival of the Amer-ican Community (Simon and Schuster New York)

Rao H Monin P Durand R (2005) Border crossing Bricolage and theerosion of categorical boundaries in French gastronomy AmerSociol Rev 70(6)968ndash91

Reay T Golden-Biddle K Germann K (2006) Legitimizing a new roleSmall wins and microprocesses of change Acad Management J49(5)977ndash998

Renzulli LA Aldrich H Moody J (2000) Family matters Gen-der networks and entrepreneurial outcomes Soc Forces 79(2)523ndash546

Reskin BF Roos PA (1990) Job Queues Gender Queues ExplainingWomenrsquos Inroad into Male Occupations (Temple University PressPhiladelphia)

Richardson JG Hatcher BW (1983) The feminization of public schoolteaching 1870ndash1920 Work Occupations 10(1)81ndash99

Ridgeway CL (2001) Gender status and leadership J Soc Issues57(4)637ndash655

Ridgeway CL (2009) Framed before we know it How gender shapessocial relations Gender Soc 23(2)145ndash160

Ridgeway CL (2011) Framed by Gender How Gender Inequality Persistsin the Modern World (Oxford University Press Oxford UK)

Ridgeway CL (2013) Why status matters for inequality Amer SociolRev 79(1)1ndash16

Ridgeway CL Correll SJ (2004) Unpacking the gender system Atheoretical perspective on gender beliefs and social relationsGender Soc 18(4)510ndash531

Ridgeway CL Correll SJ (2006) Consensus and the creation of statusbeliefs Soc Forces 85(1)431ndash453

Ridgeway CL England P (2007) Sociological approaches to sex dis-crimination in employment Crosby FJ Stockdale MS Ropp SAeds Sex Discrimination in the Workplace Multidisciplinary Perspec-tives (Blackwell Publishing Malden MA) 189ndash211

Ridgeway CL SmithndashLovin L (1999) The gender system and interac-tion Annual Rev Sociol 25(1)191ndash216

Ridgeway CL Backor K Li YE Tinkler JE Erickson KG (2009) Howeasily does a social difference become a status distinction Gen-der matters Amer Sociol Rev 74(1)44ndash62

Robb AM Watson J (2012) Gender differences in firm performanceEvidence from new ventures in the United States J Bus Ventur-ing 27(5)544ndash558

Rudman LAGlick P (2001) Prescriptive gender stereotypes and back-lash toward agentic women J Soc Issues 57(4)743ndash762

Rudman LA Phelan JE (2008) Backlash effects for disconfirming gen-der stereotypes in organizations Res Organ Behav 28(1)61ndash79

Ruef M (2010) The Entrepreneurial Group Social Identities Relationsand Collective Action (Princeton University Press Princeton NJ)

Ruef M Aldrich HE Carter NM (2003) The structure of found-ing teams Homophily strong ties and isolation among USentrepreneurs Amer Sociol Rev 68(2)195ndash222

Salamon LM Anheier HK (1997) Defining the nonprofit sector A cross-national analysis (Manchester University Press Manchester UK)

Saxenian A (1996) Beyond boundaries Open labor markets andlearning in Silicon Valley Arthur MB Rousseau DM eds TheBoundaryless Career A New Employment Principle for a New Orga-nizational Era (Oxford University Press New York) 23ndash39

Schein VE (2001) A global look at psychological barriers to womenrsquosprogress in management J Soc Issues 57(4)675ndash688

Sczesny S (2003) A closer look beneath the surface Various facetsof the think-manager-think-male stereotype Sex Roles 49(7ndash8)353ndash363

Sharir M Lerner M (2006) Gauging the success of social venturesinitiated by individual social entrepreneurs J World Bus 41(1)6ndash20

Skocpol T (2003) Diminished Democracy From Membership to Man-agement in American Civic Life (University of Oklahoma PressNorman)

Smith SR Lipsky M (1993) Nonprofits for Hire The Welfare State in theAge of Contracting (Harvard University Press Cambridge MA)

Social Security Administration (2016) National data on the relativefrequency of given names in the population of US births wherethe individual has a social security number Accessed July 312017 httpswwwssagovoactbabynameslimitshtml

Stone P (2007) Opting Out Why Women Really Quit Careers and HeadHome (University of California Press Berkeley)

Stuart TE Sorenson O (2003) Liquidity events and the geographicdistribution of entrepreneurial activity Admin Sci Quart48(2)175ndash201

Theacutebaud S (2010) Masculinity bargaining and breadwinning Un-derstanding menrsquos housework in the cultural context of paidwork Gender Soc 24(3)330ndash354

Theacutebaud S (2015) Business as plan B Institutional foundations ofgender inequality in entrepreneurship across 24 industrializedcountries Admin Sci Quart 60(4)671ndash711

Theacutebaud S Sharkey AJ (2016) Unequal hard times The influence ofthe Great Recession on gender bias in entrepreneurial financingSociol Sci 3(1)1ndash31

Themudo NS (2009) Gender and the nonprofit sector Nonprofit Vol-untary Sector Quart 38(4)663ndash683

Tilcsik A Marquis C (2013) Punctuated generosity How megandashevents and natural disasters affect corporate philanthropy inUS communities Admin Sci Quart 58(1)111ndash148

TownsendDMHart TA (2008) Perceived institutional ambiguity andthe choice of organizational form in social entrepreneurial ven-tures Entrepreneurship Theory Practice 32(4)685ndash700

Tracey P Phillips N Jarvis O (2011) Bridging institutional entrepre-neurship and the creation of new organizational forms A mul-tilevel model Organ Sci 22(1)60ndash80

Urban Institute (2008) The NCCS-GuideStar National NonprofitResearch Database National Center for Charitable StatisticsUrban Institute Washington DC

Urban Institute (2014) Statistics of income National Center for Char-itable Statistics Urban Institute Washington DC

US Census Bureau (1995) Frequently occurring surnames fromcensus 1990 Accessed July 31 2017 httpswwwcensusgovtopicspopulationgenealogydata1990_census1990_census_namefileshtml

US Census Bureau (2007) Survey of business owners and self-employed persons (SBO) Accessed July 31 2017 httpswwwcensusgovprograms-surveyssbohtml

Walker ET McCarthy JD (2010) Legitimacy strategy and resourcesin the survival of community-based organizations Soc Problems57(3)315ndash340

Weisbrod BA (1998) To Profit or Not to Profit The Commercial Trans-formation of the Nonprofit Sector (Cambridge University PressCambridge UK)

West C Zimmerman DH (1987) Doing gender Gender Soc 1(2)125ndash151

Williams CL (1992) The glass escalator Hidden advantages for menin the ldquofemalerdquo professions Soc Problems 39(3)253ndash267

Wry T York J (2017) An identity-based approach to social enterpriseAcad Management Rev 42(3)437ndash460

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Yang T Aldrich HE (2014) Whorsquos the boss Explaining genderinequality in entrepreneurial teams Amer Sociol Rev 79(2)303ndash327

Young DR (2009) Alternative perspectives on social enterpriseCordes J Steuerle E edsNonprofits and Business (Urban InstitutePress Washington DC) 21ndash46

Stefan Dimitriadis is a doctoral candidate in organiza-tional behavior at Harvard Business School His researchinterests include entrepreneurship social innovation and theway networks in communities affect organizational struc-tures and outcomes He is currently exploring these issues inthe context of entrepreneurship in Togo

Matthew Lee is assistant professor of strategy at INSEADbased in Singapore His research studies how hybrid organi-zations simultaneously pursue social and financial goals insettings including social entrepreneurship corporate social

responsibility and the commercial activities of nonprofitorganizations

Lakshmi Ramarajan is assistant professor of organiza-tional behavior at Harvard Business School She received herPhD from the Wharton School University of PennsylvaniaHer research examines the management and consequencesof individualsrsquo multiple identities in organizations (eg pro-fessional organizational racialethnic gender)

Julie Battilana is the Joseph C Wilson Professor of Busi-ness Administration at Harvard Business School and theAlan L Gleitsman Professor of Social Innovation at the Har-vard Kennedy School Her research examines hybrid orga-nizations that pursue a social mission while engaging incommercial activities to sustain their operations Her workaims to understand how these hybrids can sustainably pur-sue social and commercial goals and how they can achievehigh levels of both social and commercial performance

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ORGANIZATION SCIENCEArticles in Advance pp 1ndash21

httppubsonlineinformsorgjournalorsc ISSN 1047-7039 (print) ISSN 1526-5455 (online)

Blurring the Boundaries The Interplay of Gender and LocalCommunities in the Commercialization of Social VenturesStefan Dimitriadisa Matthew Leeb Lakshmi Ramarajana Julie Battilanaa

aOrganizational Behavior Unit Harvard Business School Boston Massachusetts 02163 b Strategy Unit INSEAD Singapore 138676Contact sdimitriadishbsedu httporcidorg0000-0003-4699-4832 (SD) matthewleeinseadedu

httporcidorg0000-0003-4772-130X (ML) lramarajanhbsedu httporcidorg0000-0002-9979-5354 (LR) jbattilanahbsedu (JB)

Received May 28 2015Revised July 13 2016 March 14 2017Accepted April 3 2017Published Online in Articles in AdvanceAugust 23 2017



Abstract This paper examines the critical role of gender in the commercialization of socialventures We argue that cultural beliefs about what is perceived to be appropriate workfor each gender influence how founders of social ventures incorporate commercial activityinto their ventures Specifically we argue and show that although cultural beliefs thatdisassociate women from commercial activitymay result in female social venture foundersbeing less likely to use commercial activity than their male counterparts these effects aremoderated by cultural beliefs about gender and commercial activity within foundersrsquo localcommunities The presence of female business owners in the same community mitigatesthe role of foundersrsquo gender on the use of commercial activity We examine these issuesthrough a novel sample of 584 social ventures in the United States We constructivelyreplicate and extend these findings with a supplemental analysis of a second samplethe full population of new nonprofit organizations founded during a two-year period inthe United States (n 31160) By highlighting how gendered aspects of both the socialand commercial sectors interact to shape the use of commercial activity by social venturefounders our findings contribute to research on hybrid organizations in the social sectorcommunities as a context for the enactment of gender and the enactment of gender inentrepreneurship

Supplemental Material The online appendix is available at httpsdoiorg101287orsc20171144

Keywords social venture bull gender bull community bull commercialization bull cultural beliefs

IntroductionThe US social sector has from its founding distin-guished itself from the commercial sector by its useof voluntary noncommercial means to pursue its civicgoals (de Tocqueville 2012) The last 30 years how-ever have seen social sector organizations increasinglyutilize commercial practices that earn revenue thusblurring the traditional boundaries between the two(Powell et al 2005 Smith and Lipsky 1993) This trendof commercialization follows declines in the chari-table resource environment (Defourny and Nyssens2006 Eikenberry and Kluver 2004 Kerlin 2006) and theimportation of business practices by managerial pro-fessionals moving into the social sector (Hwang andPowell 2009 Skocpol 2003) Commercialization is evi-dent not only in existing social sector organizationsbut in the creation of new hybrid social ventures thatpursue a social mission while engaging in commer-cial activity to sustain their operations Such venturesblend aspects of the social and commercial sectorsresulting in hybrid organizational arrangements thatcombine aspects of typical businesses and nonprof-its (Battilana and Lee 2014 Besharov and Smith 2014Pache and Santos 2013)

Hybrid social ventures possess multiple differingsets of goals andmotivations associated with the socialand commercial sectors They consequently experiencetensions between their social and commercial activitiesthat complicate organizational functioning (Battilanaet al 2015) Traditionally social welfare goals and aspirit of voluntarism have motivated the activity ofsocial sector organizations (Frumkin 2002) By con-trast efficiency and the maximization of profits haveprimarily determined the activity of commercial sec-tor organizations Intriguingly these sectoral distinc-tions parallel differences in cultural beliefs about thetypes of work considered to be appropriate for womenand men Gendered cultural beliefs associate womenwith personal qualities such as caring selflessnessand communalism (Eagly and Steffen 1984) attributesthat are consistent with the goals and motivations ofthe social sector Men on the other hand are seen tobe stereotypically competitive risk taking and agen-tic (Eagly and Karau 2002 Heilman et al 1989 Lucas2003) attributes consistent with the goals and moti-vations of the commercial sector Hence the normsthat have traditionally guided the social and commer-cial sectors mirror cultural beliefs about appropriatebehaviors for women and men respectively

1

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ved











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Table1

SummaryStatistic

sfor

Sampleof

Social

Ventures

Mean

SD

12

34

56

78

910

1112

13

1Co

mmercia

lactivity

186

5143

82

Femalefou

nder

051

7050

0minus01

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

9001

50

007

000

24

Charita

bleg

ivingperc

apita

(log)

713

1060

1minus00

07minus00

640

392

5Co

mmercia

lnonprofits(lo

gCBS

A)

minus15

55015

5minus00

270

001minus03

70minus00

016

Governm

ent-fun

dedno

nprofits(log

CBS

A)

minus04

56012

0minus00

070

011minus00

960

232

037

77

Popu

latio

n(lo

gCBS

A)

151

61127

6minus00

43minus00

010

117

019

2minus00

920

164

8Incomep

ercapita

(log

CBS

A)

103

57016

30

026minus00

320

350

063

00

008

040

10

451

9Mem

bero

fateam

018

5038

90

039minus00

690

025

000

7minus00

52minus00

680

057

003

910

Localbeneficia

ries

052

2050

00

022

003

6minus00

180

006

000

10

006minus00

54minus00

410

058

11Workedin

for-p

rofit

organizatio

n0

142

034

9minus00

300

030

001

4minus00

04minus00

110

025

002

10

005minus00

300

006

12Degreeinbu

siness

010

1030

20

107minus00

170

005minus00

56minus00

17minus00

600

023minus00

34minus00

28minus00

320

059

13AfricanAmerica

n0

330

047

1minus00

730

074minus00

03minus00

38minus00

17minus00

530

056minus00

88minus00

72minus00

42minus00

050

091

14Femalefou

ndertimesFemaleb

usinesso

wners

(meancentered

)0

000

001

00

028

001

60

687

027

9minus02

72minus01

060

065

019

0minus00

170

014

012

5minus00

480

028

Note

n

584


1 2 3









Member of a team 0109 0061 0083(0215) (0226) (0228)










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eser

ved



0010203040506070809

1 2 3 4 5

Pre

dict

ed p

roba

bilit

y










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ved



05

06

07

08

09

Pro

babi

lity

011 013 015 017 019 021


011 013 015 017 019 021


011 013 015 017 019 021



003

004

005

006

Pro

babi

lity


004

005

006

007

008

009

Pro

babi

lity


011 013 015 017 019 021


011 013 015 017 019 021


004

006

008

010

012

Pro

babi

lity


005

010

015

020

Pro

babi

lity







Dow

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from

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at 1

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Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved






Dow

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ded

from

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149

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r pe

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all

righ

ts r

eser

ved





SummaryStatistic

sfor

Sampleof

Non

profi

tOrgan

izations

Mean

SD

12

34

56

78

910

11

1Co

mmercia

lrevenue

(prop)

028

80

889

2Femaleleader

010

50

307

minus00

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

90

019

minus00

030

012

4Femaleo

fficers

presentinno

nprofit

056

90

495

minus00

020

209

minus00

045

Assets(log)

111

312

182

001

70

036

minus00

160

036

6Age

253

11

176

000

70

033

000

30

038

011

97

Governm

entsup

port

000

60

076

minus00

060

009

minus00

010

022

000

80

029

8Ch

arita

bleg

ivingperc

apita

(log

CBS

A)

245

34268

10minus00

060

014

012

2minus00

130

027

minus00

130

001

9Nonprofitp

opulation(lo

gCBS

A)

555

31

448

minus00

060

002

038

7minus00

460

007

minus00

13minus00

110

312

10Nonprofitn

iche

010

00

070

002

5minus00

14minus00

690

073

minus00

30minus00

08minus00

05minus00

53minus01

8411

Incomep

ercapita

(log

CBS

A)

104

550

176

minus00

080

018

034

7minus00

080

020

minus00

15minus00

140

372

073

1minus01

4312

Femaleleadertimes

Femaleb

usinesso

wners

(meancentered

)0

000

000

60

003

003

10

330

000

60

000

000

6minus00

010

052

013

2minus00

340

127

Note

n

311

60

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from

info

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1 2 3





Assets (log) 0007 0007 0007(0005) (0005) (0005)

Age 0003 0004 0004(0004) (00035) (0004)




Nonprofit niche 0010 0013 0015(0073) (0073) (0073)












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1 2 3 4





















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ved






















































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ved










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ved











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ved


Table1

SummaryStatistic

sfor

Sampleof

Social

Ventures

Mean

SD

12

34

56

78

910

1112

13

1Co

mmercia

lactivity

186

5143

82

Femalefou

nder

051

7050

0minus01

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

9001

50

007

000

24

Charita

bleg

ivingperc

apita

(log)

713

1060

1minus00

07minus00

640

392

5Co

mmercia

lnonprofits(lo

gCBS

A)

minus15

55015

5minus00

270

001minus03

70minus00

016

Governm

ent-fun

dedno

nprofits(log

CBS

A)

minus04

56012

0minus00

070

011minus00

960

232

037

77

Popu

latio

n(lo

gCBS

A)

151

61127

6minus00

43minus00

010

117

019

2minus00

920

164

8Incomep

ercapita

(log

CBS

A)

103

57016

30

026minus00

320

350

063

00

008

040

10

451

9Mem

bero

fateam

018

5038

90

039minus00

690

025

000

7minus00

52minus00

680

057

003

910

Localbeneficia

ries

052

2050

00

022

003

6minus00

180

006

000

10

006minus00

54minus00

410

058

11Workedin

for-p

rofit

organizatio

n0

142

034

9minus00

300

030

001

4minus00

04minus00

110

025

002

10

005minus00

300

006

12Degreeinbu

siness

010

1030

20

107minus00

170

005minus00

56minus00

17minus00

600

023minus00

34minus00

28minus00

320

059

13AfricanAmerica

n0

330

047

1minus00

730

074minus00

03minus00

38minus00

17minus00

530

056minus00

88minus00

72minus00

42minus00

050

091

14Femalefou

ndertimesFemaleb

usinesso

wners

(meancentered

)0

000

001

00

028

001

60

687

027

9minus02

72minus01

060

065

019

0minus00

170

014

012

5minus00

480

028

Note

n

584


1 2 3









Member of a team 0109 0061 0083(0215) (0226) (0228)










Dow

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from

info

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on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved



0010203040506070809

1 2 3 4 5

Pre

dict

ed p

roba

bilit

y










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info

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2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved



05

06

07

08

09

Pro

babi

lity

011 013 015 017 019 021


011 013 015 017 019 021


011 013 015 017 019 021



003

004

005

006

Pro

babi

lity


004

005

006

007

008

009

Pro

babi

lity


011 013 015 017 019 021


011 013 015 017 019 021


004

006

008

010

012

Pro

babi

lity


005

010

015

020

Pro

babi

lity







Dow

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from

info

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org

by [

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52]

on 1

9 Se

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at 1

109

Fo

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rson

al u

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nly

all

righ

ts r

eser

ved






Dow

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ded

from

info

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nly

all

righ

ts r

eser

ved





SummaryStatistic

sfor

Sampleof

Non

profi

tOrgan

izations

Mean

SD

12

34

56

78

910

11

1Co

mmercia

lrevenue

(prop)

028

80

889

2Femaleleader

010

50

307

minus00

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

90

019

minus00

030

012

4Femaleo

fficers

presentinno

nprofit

056

90

495

minus00

020

209

minus00

045

Assets(log)

111

312

182

001

70

036

minus00

160

036

6Age

253

11

176

000

70

033

000

30

038

011

97

Governm

entsup

port

000

60

076

minus00

060

009

minus00

010

022

000

80

029

8Ch

arita

bleg

ivingperc

apita

(log

CBS

A)

245

34268

10minus00

060

014

012

2minus00

130

027

minus00

130

001

9Nonprofitp

opulation(lo

gCBS

A)

555

31

448

minus00

060

002

038

7minus00

460

007

minus00

13minus00

110

312

10Nonprofitn

iche

010

00

070

002

5minus00

14minus00

690

073

minus00

30minus00

08minus00

05minus00

53minus01

8411

Incomep

ercapita

(log

CBS

A)

104

550

176

minus00

080

018

034

7minus00

080

020

minus00

15minus00

140

372

073

1minus01

4312

Femaleleadertimes

Femaleb

usinesso

wners

(meancentered

)0

000

000

60

003

003

10

330

000

60

000

000

6minus00

010

052

013

2minus00

340

127

Note

n

311

60

Dow

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from

info

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2017

at 1

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se o

nly

all

righ

ts r

eser

ved



1 2 3





Assets (log) 0007 0007 0007(0005) (0005) (0005)

Age 0003 0004 0004(0004) (00035) (0004)




Nonprofit niche 0010 0013 0015(0073) (0073) (0073)












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ved



1 2 3 4





















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ved








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ved























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2017

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Fo

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all

righ

ts r

eser

ved
























































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at 1

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Fo

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rson

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ts r

eser

ved






















































Dow

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from

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2017

at 1

109

Fo

r pe

rson

al u

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all

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ts r

eser

ved






















































Dow

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from

info

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128

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149

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9 Se

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2017

at 1

109

Fo

r pe

rson

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all

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ts r

eser

ved









Dow

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from

info

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128

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on 1

9 Se

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2017

at 1

109

Fo

r pe

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ts r

eser

ved










Dow

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from

info

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9 Se

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2017

at 1

109

Fo

r pe

rson

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all

righ

ts r

eser

ved









Dow

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from

info

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by [

128

103

149

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on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved










Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved











Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved









Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved


Table1

SummaryStatistic

sfor

Sampleof

Social

Ventures

Mean

SD

12

34

56

78

910

1112

13

1Co

mmercia

lactivity

186

5143

82

Femalefou

nder

051

7050

0minus01

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

9001

50

007

000

24

Charita

bleg

ivingperc

apita

(log)

713

1060

1minus00

07minus00

640

392

5Co

mmercia

lnonprofits(lo

gCBS

A)

minus15

55015

5minus00

270

001minus03

70minus00

016

Governm

ent-fun

dedno

nprofits(log

CBS

A)

minus04

56012

0minus00

070

011minus00

960

232

037

77

Popu

latio

n(lo

gCBS

A)

151

61127

6minus00

43minus00

010

117

019

2minus00

920

164

8Incomep

ercapita

(log

CBS

A)

103

57016

30

026minus00

320

350

063

00

008

040

10

451

9Mem

bero

fateam

018

5038

90

039minus00

690

025

000

7minus00

52minus00

680

057

003

910

Localbeneficia

ries

052

2050

00

022

003

6minus00

180

006

000

10

006minus00

54minus00

410

058

11Workedin

for-p

rofit

organizatio

n0

142

034

9minus00

300

030

001

4minus00

04minus00

110

025

002

10

005minus00

300

006

12Degreeinbu

siness

010

1030

20

107minus00

170

005minus00

56minus00

17minus00

600

023minus00

34minus00

28minus00

320

059

13AfricanAmerica

n0

330

047

1minus00

730

074minus00

03minus00

38minus00

17minus00

530

056minus00

88minus00

72minus00

42minus00

050

091

14Femalefou

ndertimesFemaleb

usinesso

wners

(meancentered

)0

000

001

00

028

001

60

687

027

9minus02

72minus01

060

065

019

0minus00

170

014

012

5minus00

480

028

Note

n

584


1 2 3









Member of a team 0109 0061 0083(0215) (0226) (0228)










Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved



0010203040506070809

1 2 3 4 5

Pre

dict

ed p

roba

bilit

y










Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved



05

06

07

08

09

Pro

babi

lity

011 013 015 017 019 021


011 013 015 017 019 021


011 013 015 017 019 021



003

004

005

006

Pro

babi

lity


004

005

006

007

008

009

Pro

babi

lity


011 013 015 017 019 021


011 013 015 017 019 021


004

006

008

010

012

Pro

babi

lity


005

010

015

020

Pro

babi

lity







Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved






Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved





SummaryStatistic

sfor

Sampleof

Non

profi

tOrgan

izations

Mean

SD

12

34

56

78

910

11

1Co

mmercia

lrevenue

(prop)

028

80

889

2Femaleleader

010

50

307

minus00

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

90

019

minus00

030

012

4Femaleo

fficers

presentinno

nprofit

056

90

495

minus00

020

209

minus00

045

Assets(log)

111

312

182

001

70

036

minus00

160

036

6Age

253

11

176

000

70

033

000

30

038

011

97

Governm

entsup

port

000

60

076

minus00

060

009

minus00

010

022

000

80

029

8Ch

arita

bleg

ivingperc

apita

(log

CBS

A)

245

34268

10minus00

060

014

012

2minus00

130

027

minus00

130

001

9Nonprofitp

opulation(lo

gCBS

A)

555

31

448

minus00

060

002

038

7minus00

460

007

minus00

13minus00

110

312

10Nonprofitn

iche

010

00

070

002

5minus00

14minus00

690

073

minus00

30minus00

08minus00

05minus00

53minus01

8411

Incomep

ercapita

(log

CBS

A)

104

550

176

minus00

080

018

034

7minus00

080

020

minus00

15minus00

140

372

073

1minus01

4312

Femaleleadertimes

Femaleb

usinesso

wners

(meancentered

)0

000

000

60

003

003

10

330

000

60

000

000

6minus00

010

052

013

2minus00

340

127

Note

n

311

60

Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved



1 2 3





Assets (log) 0007 0007 0007(0005) (0005) (0005)

Age 0003 0004 0004(0004) (00035) (0004)




Nonprofit niche 0010 0013 0015(0073) (0073) (0073)












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1 2 3 4





















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ved


Table1

SummaryStatistic

sfor

Sampleof

Social

Ventures

Mean

SD

12

34

56

78

910

1112

13

1Co

mmercia

lactivity

186

5143

82

Femalefou

nder

051

7050

0minus01

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

9001

50

007

000

24

Charita

bleg

ivingperc

apita

(log)

713

1060

1minus00

07minus00

640

392

5Co

mmercia

lnonprofits(lo

gCBS

A)

minus15

55015

5minus00

270

001minus03

70minus00

016

Governm

ent-fun

dedno

nprofits(log

CBS

A)

minus04

56012

0minus00

070

011minus00

960

232

037

77

Popu

latio

n(lo

gCBS

A)

151

61127

6minus00

43minus00

010

117

019

2minus00

920

164

8Incomep

ercapita

(log

CBS

A)

103

57016

30

026minus00

320

350

063

00

008

040

10

451

9Mem

bero

fateam

018

5038

90

039minus00

690

025

000

7minus00

52minus00

680

057

003

910

Localbeneficia

ries

052

2050

00

022

003

6minus00

180

006

000

10

006minus00

54minus00

410

058

11Workedin

for-p

rofit

organizatio

n0

142

034

9minus00

300

030

001

4minus00

04minus00

110

025

002

10

005minus00

300

006

12Degreeinbu

siness

010

1030

20

107minus00

170

005minus00

56minus00

17minus00

600

023minus00

34minus00

28minus00

320

059

13AfricanAmerica

n0

330

047

1minus00

730

074minus00

03minus00

38minus00

17minus00

530

056minus00

88minus00

72minus00

42minus00

050

091

14Femalefou

ndertimesFemaleb

usinesso

wners

(meancentered

)0

000

001

00

028

001

60

687

027

9minus02

72minus01

060

065

019

0minus00

170

014

012

5minus00

480

028

Note

n

584


1 2 3









Member of a team 0109 0061 0083(0215) (0226) (0228)










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from

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2017

at 1

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all

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ts r

eser

ved



0010203040506070809

1 2 3 4 5

Pre

dict

ed p

roba

bilit

y










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info

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Fo

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ts r

eser

ved



05

06

07

08

09

Pro

babi

lity

011 013 015 017 019 021


011 013 015 017 019 021


011 013 015 017 019 021



003

004

005

006

Pro

babi

lity


004

005

006

007

008

009

Pro

babi

lity


011 013 015 017 019 021


011 013 015 017 019 021


004

006

008

010

012

Pro

babi

lity


005

010

015

020

Pro

babi

lity







Dow

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from

info

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org

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at 1

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eser

ved






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info

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all

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ts r

eser

ved





SummaryStatistic

sfor

Sampleof

Non

profi

tOrgan

izations

Mean

SD

12

34

56

78

910

11

1Co

mmercia

lrevenue

(prop)

028

80

889

2Femaleleader

010

50

307

minus00

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

90

019

minus00

030

012

4Femaleo

fficers

presentinno

nprofit

056

90

495

minus00

020

209

minus00

045

Assets(log)

111

312

182

001

70

036

minus00

160

036

6Age

253

11

176

000

70

033

000

30

038

011

97

Governm

entsup

port

000

60

076

minus00

060

009

minus00

010

022

000

80

029

8Ch

arita

bleg

ivingperc

apita

(log

CBS

A)

245

34268

10minus00

060

014

012

2minus00

130

027

minus00

130

001

9Nonprofitp

opulation(lo

gCBS

A)

555

31

448

minus00

060

002

038

7minus00

460

007

minus00

13minus00

110

312

10Nonprofitn

iche

010

00

070

002

5minus00

14minus00

690

073

minus00

30minus00

08minus00

05minus00

53minus01

8411

Incomep

ercapita

(log

CBS

A)

104

550

176

minus00

080

018

034

7minus00

080

020

minus00

15minus00

140

372

073

1minus01

4312

Femaleleadertimes

Femaleb

usinesso

wners

(meancentered

)0

000

000

60

003

003

10

330

000

60

000

000

6minus00

010

052

013

2minus00

340

127

Note

n

311

60

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ts r

eser

ved



1 2 3





Assets (log) 0007 0007 0007(0005) (0005) (0005)

Age 0003 0004 0004(0004) (00035) (0004)




Nonprofit niche 0010 0013 0015(0073) (0073) (0073)












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1 2 3 4





















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ved























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eser

ved
























































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ved






















































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ved






















































Dow

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ved









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at 1

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eser

ved










Dow

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from

info

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by [

128

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149

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at 1

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Fo

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eser

ved











Dow

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ded

from

info

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by [

128

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149

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9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

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all

righ

ts r

eser

ved









Dow

nloa

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from

info

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org

by [

128

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149

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on 1

9 Se

ptem

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2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved


Table1

SummaryStatistic

sfor

Sampleof

Social

Ventures

Mean

SD

12

34

56

78

910

1112

13

1Co

mmercia

lactivity

186

5143

82

Femalefou

nder

051

7050

0minus01

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

9001

50

007

000

24

Charita

bleg

ivingperc

apita

(log)

713

1060

1minus00

07minus00

640

392

5Co

mmercia

lnonprofits(lo

gCBS

A)

minus15

55015

5minus00

270

001minus03

70minus00

016

Governm

ent-fun

dedno

nprofits(log

CBS

A)

minus04

56012

0minus00

070

011minus00

960

232

037

77

Popu

latio

n(lo

gCBS

A)

151

61127

6minus00

43minus00

010

117

019

2minus00

920

164

8Incomep

ercapita

(log

CBS

A)

103

57016

30

026minus00

320

350

063

00

008

040

10

451

9Mem

bero

fateam

018

5038

90

039minus00

690

025

000

7minus00

52minus00

680

057

003

910

Localbeneficia

ries

052

2050

00

022

003

6minus00

180

006

000

10

006minus00

54minus00

410

058

11Workedin

for-p

rofit

organizatio

n0

142

034

9minus00

300

030

001

4minus00

04minus00

110

025

002

10

005minus00

300

006

12Degreeinbu

siness

010

1030

20

107minus00

170

005minus00

56minus00

17minus00

600

023minus00

34minus00

28minus00

320

059

13AfricanAmerica

n0

330

047

1minus00

730

074minus00

03minus00

38minus00

17minus00

530

056minus00

88minus00

72minus00

42minus00

050

091

14Femalefou

ndertimesFemaleb

usinesso

wners

(meancentered

)0

000

001

00

028

001

60

687

027

9minus02

72minus01

060

065

019

0minus00

170

014

012

5minus00

480

028

Note

n

584


1 2 3









Member of a team 0109 0061 0083(0215) (0226) (0228)










Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved



0010203040506070809

1 2 3 4 5

Pre

dict

ed p

roba

bilit

y










Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved



05

06

07

08

09

Pro

babi

lity

011 013 015 017 019 021


011 013 015 017 019 021


011 013 015 017 019 021



003

004

005

006

Pro

babi

lity


004

005

006

007

008

009

Pro

babi

lity


011 013 015 017 019 021


011 013 015 017 019 021


004

006

008

010

012

Pro

babi

lity


005

010

015

020

Pro

babi

lity







Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved






Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved





SummaryStatistic

sfor

Sampleof

Non

profi

tOrgan

izations

Mean

SD

12

34

56

78

910

11

1Co

mmercia

lrevenue

(prop)

028

80

889

2Femaleleader

010

50

307

minus00

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

90

019

minus00

030

012

4Femaleo

fficers

presentinno

nprofit

056

90

495

minus00

020

209

minus00

045

Assets(log)

111

312

182

001

70

036

minus00

160

036

6Age

253

11

176

000

70

033

000

30

038

011

97

Governm

entsup

port

000

60

076

minus00

060

009

minus00

010

022

000

80

029

8Ch

arita

bleg

ivingperc

apita

(log

CBS

A)

245

34268

10minus00

060

014

012

2minus00

130

027

minus00

130

001

9Nonprofitp

opulation(lo

gCBS

A)

555

31

448

minus00

060

002

038

7minus00

460

007

minus00

13minus00

110

312

10Nonprofitn

iche

010

00

070

002

5minus00

14minus00

690

073

minus00

30minus00

08minus00

05minus00

53minus01

8411

Incomep

ercapita

(log

CBS

A)

104

550

176

minus00

080

018

034

7minus00

080

020

minus00

15minus00

140

372

073

1minus01

4312

Femaleleadertimes

Femaleb

usinesso

wners

(meancentered

)0

000

000

60

003

003

10

330

000

60

000

000

6minus00

010

052

013

2minus00

340

127

Note

n

311

60

Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved



1 2 3





Assets (log) 0007 0007 0007(0005) (0005) (0005)

Age 0003 0004 0004(0004) (00035) (0004)




Nonprofit niche 0010 0013 0015(0073) (0073) (0073)












Dow

nloa

ded

from

info

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org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved



1 2 3 4





















Dow

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ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved








Dow

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from

info

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by [

128

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149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved









Dow

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ded

from

info

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org

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128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

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nly

all

righ

ts r

eser

ved























Dow

nloa

ded

from

info

rms

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by [

128

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ved
























































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ved


Table1

SummaryStatistic

sfor

Sampleof

Social

Ventures

Mean

SD

12

34

56

78

910

1112

13

1Co

mmercia

lactivity

186

5143

82

Femalefou

nder

051

7050

0minus01

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

9001

50

007

000

24

Charita

bleg

ivingperc

apita

(log)

713

1060

1minus00

07minus00

640

392

5Co

mmercia

lnonprofits(lo

gCBS

A)

minus15

55015

5minus00

270

001minus03

70minus00

016

Governm

ent-fun

dedno

nprofits(log

CBS

A)

minus04

56012

0minus00

070

011minus00

960

232

037

77

Popu

latio

n(lo

gCBS

A)

151

61127

6minus00

43minus00

010

117

019

2minus00

920

164

8Incomep

ercapita

(log

CBS

A)

103

57016

30

026minus00

320

350

063

00

008

040

10

451

9Mem

bero

fateam

018

5038

90

039minus00

690

025

000

7minus00

52minus00

680

057

003

910

Localbeneficia

ries

052

2050

00

022

003

6minus00

180

006

000

10

006minus00

54minus00

410

058

11Workedin

for-p

rofit

organizatio

n0

142

034

9minus00

300

030

001

4minus00

04minus00

110

025

002

10

005minus00

300

006

12Degreeinbu

siness

010

1030

20

107minus00

170

005minus00

56minus00

17minus00

600

023minus00

34minus00

28minus00

320

059

13AfricanAmerica

n0

330

047

1minus00

730

074minus00

03minus00

38minus00

17minus00

530

056minus00

88minus00

72minus00

42minus00

050

091

14Femalefou

ndertimesFemaleb

usinesso

wners

(meancentered

)0

000

001

00

028

001

60

687

027

9minus02

72minus01

060

065

019

0minus00

170

014

012

5minus00

480

028

Note

n

584


1 2 3









Member of a team 0109 0061 0083(0215) (0226) (0228)










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ts r

eser

ved



0010203040506070809

1 2 3 4 5

Pre

dict

ed p

roba

bilit

y










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ved



05

06

07

08

09

Pro

babi

lity

011 013 015 017 019 021


011 013 015 017 019 021


011 013 015 017 019 021



003

004

005

006

Pro

babi

lity


004

005

006

007

008

009

Pro

babi

lity


011 013 015 017 019 021


011 013 015 017 019 021


004

006

008

010

012

Pro

babi

lity


005

010

015

020

Pro

babi

lity







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info

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ved






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all

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ts r

eser

ved





SummaryStatistic

sfor

Sampleof

Non

profi

tOrgan

izations

Mean

SD

12

34

56

78

910

11

1Co

mmercia

lrevenue

(prop)

028

80

889

2Femaleleader

010

50

307

minus00

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

90

019

minus00

030

012

4Femaleo

fficers

presentinno

nprofit

056

90

495

minus00

020

209

minus00

045

Assets(log)

111

312

182

001

70

036

minus00

160

036

6Age

253

11

176

000

70

033

000

30

038

011

97

Governm

entsup

port

000

60

076

minus00

060

009

minus00

010

022

000

80

029

8Ch

arita

bleg

ivingperc

apita

(log

CBS

A)

245

34268

10minus00

060

014

012

2minus00

130

027

minus00

130

001

9Nonprofitp

opulation(lo

gCBS

A)

555

31

448

minus00

060

002

038

7minus00

460

007

minus00

13minus00

110

312

10Nonprofitn

iche

010

00

070

002

5minus00

14minus00

690

073

minus00

30minus00

08minus00

05minus00

53minus01

8411

Incomep

ercapita

(log

CBS

A)

104

550

176

minus00

080

018

034

7minus00

080

020

minus00

15minus00

140

372

073

1minus01

4312

Femaleleadertimes

Femaleb

usinesso

wners

(meancentered

)0

000

000

60

003

003

10

330

000

60

000

000

6minus00

010

052

013

2minus00

340

127

Note

n

311

60

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ts r

eser

ved



1 2 3





Assets (log) 0007 0007 0007(0005) (0005) (0005)

Age 0003 0004 0004(0004) (00035) (0004)




Nonprofit niche 0010 0013 0015(0073) (0073) (0073)












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1 2 3 4





















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ved









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ved























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ved
























































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ved






















































Dow

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by [

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at 1

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ved









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info

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ved









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at 1

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all

righ

ts r

eser

ved


Table1

SummaryStatistic

sfor

Sampleof

Social

Ventures

Mean

SD

12

34

56

78

910

1112

13

1Co

mmercia

lactivity

186

5143

82

Femalefou

nder

051

7050

0minus01

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

9001

50

007

000

24

Charita

bleg

ivingperc

apita

(log)

713

1060

1minus00

07minus00

640

392

5Co

mmercia

lnonprofits(lo

gCBS

A)

minus15

55015

5minus00

270

001minus03

70minus00

016

Governm

ent-fun

dedno

nprofits(log

CBS

A)

minus04

56012

0minus00

070

011minus00

960

232

037

77

Popu

latio

n(lo

gCBS

A)

151

61127

6minus00

43minus00

010

117

019

2minus00

920

164

8Incomep

ercapita

(log

CBS

A)

103

57016

30

026minus00

320

350

063

00

008

040

10

451

9Mem

bero

fateam

018

5038

90

039minus00

690

025

000

7minus00

52minus00

680

057

003

910

Localbeneficia

ries

052

2050

00

022

003

6minus00

180

006

000

10

006minus00

54minus00

410

058

11Workedin

for-p

rofit

organizatio

n0

142

034

9minus00

300

030

001

4minus00

04minus00

110

025

002

10

005minus00

300

006

12Degreeinbu

siness

010

1030

20

107minus00

170

005minus00

56minus00

17minus00

600

023minus00

34minus00

28minus00

320

059

13AfricanAmerica

n0

330

047

1minus00

730

074minus00

03minus00

38minus00

17minus00

530

056minus00

88minus00

72minus00

42minus00

050

091

14Femalefou

ndertimesFemaleb

usinesso

wners

(meancentered

)0

000

001

00

028

001

60

687

027

9minus02

72minus01

060

065

019

0minus00

170

014

012

5minus00

480

028

Note

n

584


1 2 3









Member of a team 0109 0061 0083(0215) (0226) (0228)










Dow

nloa

ded

from

info

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org

by [

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on 1

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2017

at 1

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Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved



0010203040506070809

1 2 3 4 5

Pre

dict

ed p

roba

bilit

y










Dow

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ded

from

info

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org

by [

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on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved



05

06

07

08

09

Pro

babi

lity

011 013 015 017 019 021


011 013 015 017 019 021


011 013 015 017 019 021



003

004

005

006

Pro

babi

lity


004

005

006

007

008

009

Pro

babi

lity


011 013 015 017 019 021


011 013 015 017 019 021


004

006

008

010

012

Pro

babi

lity


005

010

015

020

Pro

babi

lity







Dow

nloa

ded

from

info

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org

by [

128

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149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

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all

righ

ts r

eser

ved






Dow

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ded

from

info

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org

by [

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149

52]

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9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved





SummaryStatistic

sfor

Sampleof

Non

profi

tOrgan

izations

Mean

SD

12

34

56

78

910

11

1Co

mmercia

lrevenue

(prop)

028

80

889

2Femaleleader

010

50

307

minus00

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

90

019

minus00

030

012

4Femaleo

fficers

presentinno

nprofit

056

90

495

minus00

020

209

minus00

045

Assets(log)

111

312

182

001

70

036

minus00

160

036

6Age

253

11

176

000

70

033

000

30

038

011

97

Governm

entsup

port

000

60

076

minus00

060

009

minus00

010

022

000

80

029

8Ch

arita

bleg

ivingperc

apita

(log

CBS

A)

245

34268

10minus00

060

014

012

2minus00

130

027

minus00

130

001

9Nonprofitp

opulation(lo

gCBS

A)

555

31

448

minus00

060

002

038

7minus00

460

007

minus00

13minus00

110

312

10Nonprofitn

iche

010

00

070

002

5minus00

14minus00

690

073

minus00

30minus00

08minus00

05minus00

53minus01

8411

Incomep

ercapita

(log

CBS

A)

104

550

176

minus00

080

018

034

7minus00

080

020

minus00

15minus00

140

372

073

1minus01

4312

Femaleleadertimes

Femaleb

usinesso

wners

(meancentered

)0

000

000

60

003

003

10

330

000

60

000

000

6minus00

010

052

013

2minus00

340

127

Note

n

311

60

Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved



1 2 3





Assets (log) 0007 0007 0007(0005) (0005) (0005)

Age 0003 0004 0004(0004) (00035) (0004)




Nonprofit niche 0010 0013 0015(0073) (0073) (0073)












Dow

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from

info

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2017

at 1

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Fo

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all

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eser

ved



1 2 3 4





















Dow

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info

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2017

at 1

109

Fo

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ts r

eser

ved








Dow

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from

info

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9 Se

ptem

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2017

at 1

109

Fo

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all

righ

ts r

eser

ved









Dow

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from

info

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org

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149

52]

on 1

9 Se

ptem

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2017

at 1

109

Fo

r pe

rson

al u

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nly

all

righ

ts r

eser

ved























Dow

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from

info

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103

149

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on 1

9 Se

ptem

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2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved
























































Dow

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from

info

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128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved






















































Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved






















































Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved









Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

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2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved


Table1

SummaryStatistic

sfor

Sampleof

Social

Ventures

Mean

SD

12

34

56

78

910

1112

13

1Co

mmercia

lactivity

186

5143

82

Femalefou

nder

051

7050

0minus01

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

9001

50

007

000

24

Charita

bleg

ivingperc

apita

(log)

713

1060

1minus00

07minus00

640

392

5Co

mmercia

lnonprofits(lo

gCBS

A)

minus15

55015

5minus00

270

001minus03

70minus00

016

Governm

ent-fun

dedno

nprofits(log

CBS

A)

minus04

56012

0minus00

070

011minus00

960

232

037

77

Popu

latio

n(lo

gCBS

A)

151

61127

6minus00

43minus00

010

117

019

2minus00

920

164

8Incomep

ercapita

(log

CBS

A)

103

57016

30

026minus00

320

350

063

00

008

040

10

451

9Mem

bero

fateam

018

5038

90

039minus00

690

025

000

7minus00

52minus00

680

057

003

910

Localbeneficia

ries

052

2050

00

022

003

6minus00

180

006

000

10

006minus00

54minus00

410

058

11Workedin

for-p

rofit

organizatio

n0

142

034

9minus00

300

030

001

4minus00

04minus00

110

025

002

10

005minus00

300

006

12Degreeinbu

siness

010

1030

20

107minus00

170

005minus00

56minus00

17minus00

600

023minus00

34minus00

28minus00

320

059

13AfricanAmerica

n0

330

047

1minus00

730

074minus00

03minus00

38minus00

17minus00

530

056minus00

88minus00

72minus00

42minus00

050

091

14Femalefou

ndertimesFemaleb

usinesso

wners

(meancentered

)0

000

001

00

028

001

60

687

027

9minus02

72minus01

060

065

019

0minus00

170

014

012

5minus00

480

028

Note

n

584


1 2 3









Member of a team 0109 0061 0083(0215) (0226) (0228)










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eser

ved



0010203040506070809

1 2 3 4 5

Pre

dict

ed p

roba

bilit

y










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info

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org

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eser

ved



05

06

07

08

09

Pro

babi

lity

011 013 015 017 019 021


011 013 015 017 019 021


011 013 015 017 019 021



003

004

005

006

Pro

babi

lity


004

005

006

007

008

009

Pro

babi

lity


011 013 015 017 019 021


011 013 015 017 019 021


004

006

008

010

012

Pro

babi

lity


005

010

015

020

Pro

babi

lity







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ved






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9 Se

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2017

at 1

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al u

se o

nly

all

righ

ts r

eser

ved





SummaryStatistic

sfor

Sampleof

Non

profi

tOrgan

izations

Mean

SD

12

34

56

78

910

11

1Co

mmercia

lrevenue

(prop)

028

80

889

2Femaleleader

010

50

307

minus00

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

90

019

minus00

030

012

4Femaleo

fficers

presentinno

nprofit

056

90

495

minus00

020

209

minus00

045

Assets(log)

111

312

182

001

70

036

minus00

160

036

6Age

253

11

176

000

70

033

000

30

038

011

97

Governm

entsup

port

000

60

076

minus00

060

009

minus00

010

022

000

80

029

8Ch

arita

bleg

ivingperc

apita

(log

CBS

A)

245

34268

10minus00

060

014

012

2minus00

130

027

minus00

130

001

9Nonprofitp

opulation(lo

gCBS

A)

555

31

448

minus00

060

002

038

7minus00

460

007

minus00

13minus00

110

312

10Nonprofitn

iche

010

00

070

002

5minus00

14minus00

690

073

minus00

30minus00

08minus00

05minus00

53minus01

8411

Incomep

ercapita

(log

CBS

A)

104

550

176

minus00

080

018

034

7minus00

080

020

minus00

15minus00

140

372

073

1minus01

4312

Femaleleadertimes

Femaleb

usinesso

wners

(meancentered

)0

000

000

60

003

003

10

330

000

60

000

000

6minus00

010

052

013

2minus00

340

127

Note

n

311

60

Dow

nloa

ded

from

info

rms

org

by [

128

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149

52]

on 1

9 Se

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ber

2017

at 1

109

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al u

se o

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all

righ

ts r

eser

ved



1 2 3





Assets (log) 0007 0007 0007(0005) (0005) (0005)

Age 0003 0004 0004(0004) (00035) (0004)




Nonprofit niche 0010 0013 0015(0073) (0073) (0073)












Dow

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ved



1 2 3 4





















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ved








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ved









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ved























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ved
























































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2017

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ved






















































Dow

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ved






















































Dow

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2017

at 1

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Fo

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ved









Dow

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info

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at 1

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ts r

eser

ved



0010203040506070809

1 2 3 4 5

Pre

dict

ed p

roba

bilit

y










Dow

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from

info

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by [

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9 Se

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2017

at 1

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Fo

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al u

se o

nly

all

righ

ts r

eser

ved



05

06

07

08

09

Pro

babi

lity

011 013 015 017 019 021


011 013 015 017 019 021


011 013 015 017 019 021



003

004

005

006

Pro

babi

lity


004

005

006

007

008

009

Pro

babi

lity


011 013 015 017 019 021


011 013 015 017 019 021


004

006

008

010

012

Pro

babi

lity


005

010

015

020

Pro

babi

lity







Dow

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from

info

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org

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at 1

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ved






Dow

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info

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9 Se

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2017

at 1

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Fo

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al u

se o

nly

all

righ

ts r

eser

ved





SummaryStatistic

sfor

Sampleof

Non

profi

tOrgan

izations

Mean

SD

12

34

56

78

910

11

1Co

mmercia

lrevenue

(prop)

028

80

889

2Femaleleader

010

50

307

minus00

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

90

019

minus00

030

012

4Femaleo

fficers

presentinno

nprofit

056

90

495

minus00

020

209

minus00

045

Assets(log)

111

312

182

001

70

036

minus00

160

036

6Age

253

11

176

000

70

033

000

30

038

011

97

Governm

entsup

port

000

60

076

minus00

060

009

minus00

010

022

000

80

029

8Ch

arita

bleg

ivingperc

apita

(log

CBS

A)

245

34268

10minus00

060

014

012

2minus00

130

027

minus00

130

001

9Nonprofitp

opulation(lo

gCBS

A)

555

31

448

minus00

060

002

038

7minus00

460

007

minus00

13minus00

110

312

10Nonprofitn

iche

010

00

070

002

5minus00

14minus00

690

073

minus00

30minus00

08minus00

05minus00

53minus01

8411

Incomep

ercapita

(log

CBS

A)

104

550

176

minus00

080

018

034

7minus00

080

020

minus00

15minus00

140

372

073

1minus01

4312

Femaleleadertimes

Femaleb

usinesso

wners

(meancentered

)0

000

000

60

003

003

10

330

000

60

000

000

6minus00

010

052

013

2minus00

340

127

Note

n

311

60

Dow

nloa

ded

from

info

rms

org

by [

128

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149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

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rson

al u

se o

nly

all

righ

ts r

eser

ved



1 2 3





Assets (log) 0007 0007 0007(0005) (0005) (0005)

Age 0003 0004 0004(0004) (00035) (0004)




Nonprofit niche 0010 0013 0015(0073) (0073) (0073)












Dow

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ved



1 2 3 4





















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ved









Dow

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at 1

109

Fo

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all

righ

ts r

eser

ved























Dow

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by [

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9 Se

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2017

at 1

109

Fo

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all

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ts r

eser

ved
























































Dow

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Fo

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ved






















































Dow

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Fo

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ved






















































Dow

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info

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Fo

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ved









Dow

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info

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by [

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9 Se

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2017

at 1

109

Fo

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rson

al u

se o

nly

all

righ

ts r

eser

ved



05

06

07

08

09

Pro

babi

lity

011 013 015 017 019 021


011 013 015 017 019 021


011 013 015 017 019 021



003

004

005

006

Pro

babi

lity


004

005

006

007

008

009

Pro

babi

lity


011 013 015 017 019 021


011 013 015 017 019 021


004

006

008

010

012

Pro

babi

lity


005

010

015

020

Pro

babi

lity







Dow

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from

info

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org

by [

128

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on 1

9 Se

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2017

at 1

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Fo

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eser

ved






Dow

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ded

from

info

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org

by [

128

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52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved





SummaryStatistic

sfor

Sampleof

Non

profi

tOrgan

izations

Mean

SD

12

34

56

78

910

11

1Co

mmercia

lrevenue

(prop)

028

80

889

2Femaleleader

010

50

307

minus00

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

90

019

minus00

030

012

4Femaleo

fficers

presentinno

nprofit

056

90

495

minus00

020

209

minus00

045

Assets(log)

111

312

182

001

70

036

minus00

160

036

6Age

253

11

176

000

70

033

000

30

038

011

97

Governm

entsup

port

000

60

076

minus00

060

009

minus00

010

022

000

80

029

8Ch

arita

bleg

ivingperc

apita

(log

CBS

A)

245

34268

10minus00

060

014

012

2minus00

130

027

minus00

130

001

9Nonprofitp

opulation(lo

gCBS

A)

555

31

448

minus00

060

002

038

7minus00

460

007

minus00

13minus00

110

312

10Nonprofitn

iche

010

00

070

002

5minus00

14minus00

690

073

minus00

30minus00

08minus00

05minus00

53minus01

8411

Incomep

ercapita

(log

CBS

A)

104

550

176

minus00

080

018

034

7minus00

080

020

minus00

15minus00

140

372

073

1minus01

4312

Femaleleadertimes

Femaleb

usinesso

wners

(meancentered

)0

000

000

60

003

003

10

330

000

60

000

000

6minus00

010

052

013

2minus00

340

127

Note

n

311

60

Dow

nloa

ded

from

info

rms

org

by [

128

103

149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved



1 2 3





Assets (log) 0007 0007 0007(0005) (0005) (0005)

Age 0003 0004 0004(0004) (00035) (0004)




Nonprofit niche 0010 0013 0015(0073) (0073) (0073)












Dow

nloa

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from

info

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org

by [

128

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on 1

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2017

at 1

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Fo

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rson

al u

se o

nly

all

righ

ts r

eser

ved



1 2 3 4





















Dow

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info

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org

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at 1

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ved








Dow

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Fo

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ved









Dow

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109

Fo

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ts r

eser

ved























Dow

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info

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2017

at 1

109

Fo

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ts r

eser

ved
























































Dow

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info

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at 1

109

Fo

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ved






















































Dow

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info

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2017

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109

Fo

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ved






















































Dow

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info

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9 Se

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2017

at 1

109

Fo

r pe

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eser

ved









Dow

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from

info

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128

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2017

at 1

109

Fo

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ts r

eser

ved






Dow

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ded

from

info

rms

org

by [

128

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149

52]

on 1

9 Se

ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved





SummaryStatistic

sfor

Sampleof

Non

profi

tOrgan

izations

Mean

SD

12

34

56

78

910

11

1Co

mmercia

lrevenue

(prop)

028

80

889

2Femaleleader

010

50

307

minus00

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

90

019

minus00

030

012

4Femaleo

fficers

presentinno

nprofit

056

90

495

minus00

020

209

minus00

045

Assets(log)

111

312

182

001

70

036

minus00

160

036

6Age

253

11

176

000

70

033

000

30

038

011

97

Governm

entsup

port

000

60

076

minus00

060

009

minus00

010

022

000

80

029

8Ch

arita

bleg

ivingperc

apita

(log

CBS

A)

245

34268

10minus00

060

014

012

2minus00

130

027

minus00

130

001

9Nonprofitp

opulation(lo

gCBS

A)

555

31

448

minus00

060

002

038

7minus00

460

007

minus00

13minus00

110

312

10Nonprofitn

iche

010

00

070

002

5minus00

14minus00

690

073

minus00

30minus00

08minus00

05minus00

53minus01

8411

Incomep

ercapita

(log

CBS

A)

104

550

176

minus00

080

018

034

7minus00

080

020

minus00

15minus00

140

372

073

1minus01

4312

Femaleleadertimes

Femaleb

usinesso

wners

(meancentered

)0

000

000

60

003

003

10

330

000

60

000

000

6minus00

010

052

013

2minus00

340

127

Note

n

311

60

Dow

nloa

ded

from

info

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org

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128

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ber

2017

at 1

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Fo

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ts r

eser

ved



1 2 3





Assets (log) 0007 0007 0007(0005) (0005) (0005)

Age 0003 0004 0004(0004) (00035) (0004)




Nonprofit niche 0010 0013 0015(0073) (0073) (0073)












Dow

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1 2 3 4





















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SummaryStatistic

sfor

Sampleof

Non

profi

tOrgan

izations

Mean

SD

12

34

56

78

910

11

1Co

mmercia

lrevenue

(prop)

028

80

889

2Femaleleader

010

50

307

minus00

173

Femaleb

usinesso

wners

(prop

CBS

A)

015

90

019

minus00

030

012

4Femaleo

fficers

presentinno

nprofit

056

90

495

minus00

020

209

minus00

045

Assets(log)

111

312

182

001

70

036

minus00

160

036

6Age

253

11

176

000

70

033

000

30

038

011

97

Governm

entsup

port

000

60

076

minus00

060

009

minus00

010

022

000

80

029

8Ch

arita

bleg

ivingperc

apita

(log

CBS

A)

245

34268

10minus00

060

014

012

2minus00

130

027

minus00

130

001

9Nonprofitp

opulation(lo

gCBS

A)

555

31

448

minus00

060

002

038

7minus00

460

007

minus00

13minus00

110

312

10Nonprofitn

iche

010

00

070

002

5minus00

14minus00

690

073

minus00

30minus00

08minus00

05minus00

53minus01

8411

Incomep

ercapita

(log

CBS

A)

104

550

176

minus00

080

018

034

7minus00

080

020

minus00

15minus00

140

372

073

1minus01

4312

Femaleleadertimes

Femaleb

usinesso

wners

(meancentered

)0

000

000

60

003

003

10

330

000

60

000

000

6minus00

010

052

013

2minus00

340

127

Note

n

311

60

Dow

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ded

from

info

rms

org

by [

128

103

149

52]

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ptem

ber

2017

at 1

109

Fo

r pe

rson

al u

se o

nly

all

righ

ts r

eser

ved



1 2 3





Assets (log) 0007 0007 0007(0005) (0005) (0005)

Age 0003 0004 0004(0004) (00035) (0004)




Nonprofit niche 0010 0013 0015(0073) (0073) (0073)












Dow

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1 2 3 4





















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ved



1 2 3





Assets (log) 0007 0007 0007(0005) (0005) (0005)

Age 0003 0004 0004(0004) (00035) (0004)




Nonprofit niche 0010 0013 0015(0073) (0073) (0073)












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blurring the boundaries: the interplay of gender and local ... files/blurring the boundaries... ·...

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