Models and forms of financing offered by institutional funds, VC funds and business angels with respect to the commercialization of R&D results are not suitable for high-tech startup projects.They do not meet the requirements of their initiators, fail to satisfy the conditions or keep up with the trends in the market of innovations.
There is no opportunity to get the general public involved in the process of financing innovations. There are no cross-border and universal regulations for investors (in terms of cost and investment business entry rules). The existing limitations for those who want to invest in high-tech products, breakthrough technologies are among the main problems of investment in innovations.
Institutional investors and private equity representatives may not have a deep understanding of new, rapidly developing scientific disciplines. Investment decisions are often made regarding a package of investment proposals, without in-depth analysis, somewhat intuitively.
To make an investment decision on the innovations and the relevance of commercialization, potential investors need to obtain an independent expert opinion, which is expensive and time-consuming. Obtaining such opinions may result in a breach of confidentiality with respect to know-how and innovations.
Additionaly, due to the above-mentioned factors, there may be prerequisites for our potential competitors to prevent the implementation of innovation projects. These competitors may include, among others, companies with established economic strategies that traditionally monopolize the respective markets.
To adequately assess the potential for the commercialization of high-tech innovations, taking into account the specifics of R&D by industry, the level of risk, the depth of R&D – their breakthrough or local nature – we need an artificial intelligence software (so far unavailable) using the mathematical models of fuzzy sets, criteria importance theory and neutrosophy. The ability to objectively and timely determine the feasibility of commercializing new technologies to avoid bad investment decisions is a key indicator of the Ecosystem's management quality.