| dc.description.abstract | Meaningful correlation between technological and financial performances is
important to management of technology and innovation. The technological
performance of a firm could be represented by its patent portfolio since the patented
inventions give their owners an exclusive right to exclude others from exploiting and
commercializing them on the market, which highly influences the financial
performance. In this thesis, a new approach is proposed to analyze such a correlation
between the technological and financial performances. Our contributions are threefold. First, our approach proposes that four patent-portfolio indicators highly
correlated to the technological performance of a firm include: patent age, patent
claims, the number of inventors, and the number of patents newly applied for or
purchased. Second, these four indicators give a strong correlation with financial
performance of a firm represented by price to earnings, earning per share, stock price
on the market and other four key financial indicators (liquidity, leverage, profitability,
and valuation ratios). Third, our analysis takes into account the yearly lags of the
technology-finance correlation that happen in reality. Our proposed approach adopts
Spearman correlation coefficient, artificial neuron network and financial ratio
analysis. We experimented on two kinds of datasets: (i) the technology datasets,
including USPTO patents and UC-Berkeley patent datasets, and (ii) the financial
datasets of NASDAQ, AMEX and NYSE stock markets. Such datasets include
322,095 patents from 259 companies specialized in computer technologies in the 35-
year period (1981 – 2013). Our research outcomes could benefit CEOs, investors and
other stakeholders to design better R&D strategies for increasing their technology
values or to find their investment opportunities. | en_US |
