Biotechnology firms, signals, and venture capital investment
Abstract
Purpose: Biotechnology has gained such prominence that approximately 50% of the new drugs developed in the world are of biotechnological origin. Some of the Covid-19 vaccines are a good example of this. The biotechnology R&D projects are characterized by high costs, prolonged development times, and a high degree of uncertainty and failure. Few types of financial agents undertake such a risky investment: venture capital firms invest in high-tech, high-risk companies. In this paper, we analyze the signals that influence venture capital investment decisions.
Design/methodology/approach: Hypotheses about the effectiveness of these signals are validated by means of a probit regression with panel data on a sample of 210 biotechnology companies established in Spain over a ten-year period.
Findings: Positive and negative signalling effect has been found for some of the phenomena analysed, which validate the proposed model.
Research limitations/implications: A convenience sample has been used for methodological reasons, and some phenomena that could have some effect on the venture capital investment decisions have not been possible to observe, due to the lack of available data.
Practical implications: It can be crucial for biotechnology firms that their managers know which characteristics make these firms attractive to venture capital firms. Additionally, it is important to know those signals that, instead of favouring this investment, deter it.
Originality/value: The focus on the first venture capital investment -instead of the most usual focus on the amount invested- as an event that mitigates the information asymmetry level, the use of a probit regression with panel data, and such a quantitative analysis on the Spanish biotech industry, never done before, highlight the originality of this work.
Keywords
Full Text:
PDFDOI: https://doi.org/10.3926/ic.1978
This work is licensed under a Creative Commons Attribution 4.0 International License
Intangible Capital, 2004-2024
Online ISSN: 1697-9818; Print ISSN: 2014-3214; DL: B-33375-2004
Publisher: OmniaScience