26th International Association for Management of Technology Conference - IAMOT 2017

NASDAQ Biotechnology Index (NBI) has been more steady than Dow Jones Industrial Average. And digital technology is promoting democratic innovation. Start-ups are more excellent in speed, cost, and flexible management than large market-oriented pharmaceutical companies to integrate the innovative technology with the niche market. However, most start-ups are in negative profits except dozens of companies in the US 1500 biotech start-ups, because of ‘Death-valley’ as negative profits period for the drug development in the average 12 years, US Dollars 3 billion, and success probability one millionth. On the other side, the Crowdfunding in FinTech which has developed in digitization, is superior to collect constant funds from a large number of investors even if each small financial amount, and can function as the mediation between angel investors and venture capital (VC) by signaling, based on a virtual marketing research. As research questions, is it possible to reduce the waste of high birth and high death rate type innovation at start-ups ecosystem, by applying Bayesian Markov chain Monte Carlo (MCMC) analysis as one of artificial intelligence (AI) methods? Is there what kind of R & D investment decision difference between the present Growth type and the Stagnant type biotech start-ups, for overcoming past ‘Death-valley’ just after the financial crisis as Bankruptcy of Lehman Brothers? As a key concept, biotech start-up is defined as a portfolio of real options which assume the commercialization ideas of life science as the underlying assets. Among the NBI components, this paper selected 72 companies of which data in both FY 2009 and 2015 are available from the U.S. Securities and Exchange Commission (SEC)’s EDGAR database, classified into the Growth and the Stagnant biotech start-ups based on the increase ratio of their stock prices between FY2009 and 2015, and compared the characteristics of the research and development (R&D) investment of both type start-ups with the net income (loss), R&D expenses, and stockholders’ equity values by applying Bayesian MCMC hierarchy model. While the growth rates of stock prices in the Growth group are higher in the six years towards FY 2015 if the lower the stock prices of FY 2009, the higher the stock price of FY 2009 is, the higher the stock price of FY 2015 is, compared to the Stagnant group. In FY 2009 83% of the Stagnant group and 66% of the Growth group are, and in FY2015 72% of the Stagnant group and 52% of the Growth group are respectively deficit companies. In the 6-year net income (loss) fluctuation, there is a positive correlation between both fiscal years in the Growth group, but in the Stagnant group the correlation is weak and chaotic. There is a negative influence in the Stagnant group between the net income and R & D expenses in both fiscal years, and FY 2015 is more influential than FY 2009. On the other hand, in the Growth group, there is a positive contribution to net income by R & D expenses, and FY 2015 is more influential than FY 2009. Between net income and shareholders’ equity value, the correlation is weak and chaotic in the Stagnant group. However, in the Growth group, there is a positive and clear relationship. Thus it is possible to evaluate the potential value of even a deficit company. If FinTech can leverage the market mechanism through the Internet and the Cloud-funding management companies can adopt the screening method for the business plan by experts, a signaling function of FinTech can be expected especially for VC investment in neglected diseases.