Funding acquisition drivers for new venture firms: Diminishing value of human capital signals in early rounds of funding

  • Received December 24, 2018;
    Accepted February 1, 2019;
    Published February 15, 2019
  • Author(s)
    Snehal Shetty
    ORCID Researcher ID ,
    Ranjany Sundaram
    ORCID Researcher ID
  • DOI
    http://dx.doi.org/10.21511/ppm.17(1).2019.08
  • Article Info
    Volume 17 2019, Issue #1, pp. 78-94
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  • Cited by
    4 articles
  • 1308 Views
  • 191 Downloads

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This work is licensed under a Creative Commons Attribution 4.0 International License

Multiple factors such as human capital, amount raised in the first round, innovation etc. have an impact on the funding prospect of new ventures. This paper explored the influencing factors that drive multiple rounds of funding for new venture firms and provided a much broader perspective of funding drivers during the early stages of the new venture firm. Using signalling theory and human capital theory, this paper analyzed signals that influence the acquisition of funds in the first round and whether those signals persisted for the second and third rounds of funding when information asymmetries between the investors and new venture firms reduce. This study disentangled the signalling effects of the human capital factors across three funding rounds and proved the diminishing value of signals across each subsequent round of funding. Finding showed that the signal effect from premier institution education was the only human capital signal that persisted across each round of funding, while other signals did not persist beyond the first round of funding. In addition, new venture firms with founders educated from premier educational institutions were able to attract more investors and close more funding rounds. This study also proved that the amount raised in the first round of funding positively impacted the amounts raised in the second and third rounds stressing its importance for new venture firms. Empirical demonstration of the propositions was done with 156 new venture firms in India, the fastest growing and third largest startup ecosystem in the world.

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    • Figure 1. Signaling effects of human capital factors across multiple funding rounds and inter-funding round dependencies
    • Figure 2. Number of funding rounds closed and number of investors attracted across multiple rounds of funding
    • Figure 3. Mosaic plot showing relationships between number of funding rounds and human capital variables
    • Figure 4. Mosaic plot showing relationships between number of investors and human capital variables
    • Figure 5. Inter-funding round dependencies
    • Figure 6. Residual vs fit plot for linear regression – first round funding amount vs human capital variables
    • Table 1. Model development criteria
    • Table 2. Descriptive statistics and Pearson correlations
    • Table 3. Estimates for raising funds across multiple rounds of funding using binary logit regression
    • Table 4. Odds ratio for more than one round of funding
    • Table 5. Estimates for number of funding rounds and number of investors attracted using Poisson regression
    • Table 6. Relationships between amounts raised in each funding round
    • Table 7. Estimates for amount of funds raised across multiple rounds of funding using linear Regression
    • Table 8. Linkage of proposed method and results
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