Research ArticleSOCIAL SCIENCES

Evidence that investors penalize female founders for lack of industry fit

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Science Advances  25 Nov 2020:
Vol. 6, no. 48, eabd7664
DOI: 10.1126/sciadv.abd7664
  • Fig. 1 Study 1 female founding CEO disadvantage by industry type.

    Figure reflects average raw funding amounts as U.S. dollars in millions; P values reflect natural log of funds raised “ln funding” to account for potential skewness (38). Figure indicates that female founding CEOs raise significantly less than male founding CEOs when serving male- but not female-dominated industries. See Fig. 2 for additional comparisons.

  • Fig. 2 Study 1 lack of fit disadvantage by founding CEO gender.

    Figure reflects natural log of funds raised (ln funding); it indicates that female founding CEOs raise significantly less funding when catering to male-dominated industries that represent a lack of fit, while male founding CEOs do not raise significantly less funding when catering to female-dominated industries that are a lack of fit for them.

  • Fig. 3 Study 2 funding allocation comparisons by founding CEO type.

    Figure reflects average raw funding allocations based on $400,000 cap across all four conditions. It indicates that female founding CEOs are allocated significantly lower amounts of ln funding when catering to lack of fit male-dominated (versus female-dominated) industries, while male founding CEOs receive similar amounts regardless of industry fit. Note that female founding CEOs are also allocated significantly less than male founding CEOs for lack of fit (P < 0.001), while female founding CEOs do not receive significantly more than male founding CEOs for fit.

  • Fig. 4 Study 2 perceived fit differences by industry served.

    Perceived fit values reflect 1 to 7 rating scale measure responses provided by investors serving as experimental participants. Female founding CEOs catering to male-dominated (versus female-dominated) industries conveyed a significantly lower sense of venture-CEO fit, while perceived venture-CEO fit did not differ by industry served for male founding CEOs.

  • Table 1 Study 1 summary statistics.

    Study 1 summary statistics..

    Venture funding raised average$16,739,338
    Male-led venture funding average$18,509,448
    Female-led venture funding average$7,996,069
    Operating count214
    Closed count105
    Acquired count72
    IPO count1
    SF launch count201
    NY launch count191
    Male founding CEO count326
    Female founding CEO count66
    TCD finalist distinction count115
  • Table 2 Study 1 descriptive statistics and correlations.

    Study 1 descriptive statistics and correlations.. Ln funding (logged aggregate funds raised); BLS percentage (percentage women employed); founder gender (female founding CEO = 1); founder age category (0 to 2); launch location (0, 1); launch year (2010 to 2018); venture quality (0, 1); venture industry (1 to 12); venture “operate” operating status (0, 1). P < 0.10, *P < 0.05, **P < 0.01, and ***P < 0.001.

    MSD23456789
    1Ln funding12.645.73−0.02−0.24***0.11*0.080.010.21***0.050.28***
    2BLS percentage44.3217.850.27***0.020.010.01−0.12*−0.05−0.01
    3Founder gender0.170.370.040.040.22***−0.040.010.03
    4Founder age0.840.700.16**−0.06−0.000.080.11*
    5Launch location0.510.500.060.000.17***0.09
    6Launch year20132.350.020.090.29***
    7Venture quality0.290.460.040.07
    8Venture industry7.843.650.10*
    9Venture operate0.730.44
  • Table 3 Study 2 descriptive statistics and correlations.

    Founder “Entrep” gender, industry gender dominance, and investor gender (female = 1). Perceived fit (1 to 7 rating scale). Investor age (number of years old). Investor years of experience “Investor exper” (coded as 1 to 12, with 12 indicating “10+ years”). Investor accreditation status “Investor accred” (1 if accredited). *P < 0.05, **P < 0.01, and ***P < 0.001.

    MSD2345678910
    1Condition2.501.120.24***0.20***0.000.45***0.12**0.000.000.000.00
    2Ln funding10.862.520.47***−0.10*0.17***0.31***−0.05−0.02−0.020.10*
    3Ln valuation12.543.70−0.13**0.09*0.17***−0.02−0.06−0.04−0.10*
    4Entrep gender0.500.500.00−0.050.000.000.000.00
    5Industry gender0.500.500.070.000.000.000.00
    6Perceived fit5.231.21−0.14**−0.28***−0.22***0.33***
    7Investor gender0.320.470.030.09*−0.23***
    8Investor age51.6316.210.58***−0.42***
    9Investor exper9.013.19−0.27***
    10Investor accred0.450.50
  • Table 4 Study 1 regression results.

    ***P < 0.001. Robust standard errors clustered by venture in parentheses.

    Effect on ln
    funding:
    Model 1Model 2Model 3
    Founding CEO
    gender
    −3.75***−12.44***−10.16***
    Female = 1(0.75)(2.05)(1.97)
    Industry gender
    dominance
    −0.03−0.01
    Percentage
    women
    employed
    (0.02)(0.02)
    Founder *
    Industry
    0.16***0.12***
    Gender
    interaction
    (0.04)(0.04)
    Founding CEO
    age
    0.57
    (0.38)
    Venture launch location0.54
    (0.54)
    Venture age0.05
    (0.12)
    Venture quality2.24***
    (0.58)
    Venture industry0.01
    (0.07)
    Venture
    operating
    status
    3.17***
    (0.63)
    Intercept13.27***14.33***9.42***
    (0.31)(0.84)(1.40)
    Multiple R20.060.110.21
    Adjusted R20.060.100.20
    F statistic24.87***15.63***11.62***
  • Table 5 Study 2 linear mixed effects results.

    P < 0.10, *P < 0.05, **P < 0.01, and ***P < 0.001. Standard errors in parentheses.

    Effect onLn fundingLn valuationPerceived fit
    Founding CEO
    gender
    −1.42***−2.34***−0.37***
    Female = 1(0.30)(0.35)(0.11)
    Industry gender
    dominance
    −0.06−0.68−0.08
    Female
    dominated = 1
    (0.30)(0.35)(0.11)
    Entrepreneur *
    Industry
    1.83***2.68***0.48**
    Gender
    interaction
    (0.43)(0.50)(0.15)
    Investor gender−0.12−0.42−0.19
    Female = 1(0.24)(0.51)(0.16)
    Investor age0.00−0.03−0.01
    (0.01)(0.02)(0.01)
    Investor years of
    experience
    −0.01−0.01−0.03
    (0.04)(0.09)(0.03)
    Investor
    accreditation
    0.52*−1.20*0.58***
    (0.24)(0.52)(0.17)
    Intercept10.78***15.56***5.91***
    (0.52)(1.06)(0.34)
    Marginal R20.080.080.16
    Sample size130130130
  • Table 6 Study 2 bootstrapped multiple mediation analyses.

    R package mediation models with 10,000 bootstrapped samples, adjusted for investor gender, age, years of investing experience, and accreditation status. **P < 0.01 and ***P < 0.001. DV, dependent variables of logged funding and logged valuation; IV, independent variable of experimental condition.

    Study 2 model outcomeEffect of IV on
    mediator
    Effect of mediator on
    DV
    Indirect effect of
    mediator
    95% CI lower bound95% CI upper bound
    LnFunding0.354**0.653***0.231***0.110.37
    LnValuation0.974***0.347***0.170.55

Supplementary Materials

  • Supplementary Materials

    Evidence that investors penalize female founders for lack of industry fit

    Dana Kanze, Mark A. Conley, Tyler G. Okimoto, Damon J. Phillips, Jennifer Merluzzi

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