The Delay Effect Of Innovation Input And The Cause Of Innovation Risk

With the steady growth of our economy, innovation has becoming the important driving force of economic development and social civilization as well as getting the concern and attention from people. However, the improvement of innovative capacity will play an effective role as long as on the basis of strong material. For this reason, we should pay more attention to the innovative input and increase its proportion in GDP, which will continuously promote the improvement of innovative capacity and rapid development of economy. In recent years, R&D expenditure in China is continually growing with an average annual growth rate of 20%. Meanwhile, the average annual growth rate of R&D personnel FTE remains at 10%. However, it has become a controversial topic in academia that whether continually increasing innovation inputs can bring a rapid development to innovation ability. At the present stage, China’s market-oriented economy has the features of variability and complexity, which increase the risks and uncertainties of innovation inputs to some extent. The reason behind is mainly because of the time lag of innovation inputs, namely the innovation delay which refers to the whole process of innovation behavior from the innovation ideas to market value. Since the time cost, generated from innovation delay, adds risks and uncertainties to the innovation process, it is highly likely that they would also influence the optimal allocation of innovation resources and the maximization of economic benefits from innovation behavior. Therefore, innovation performance and improvement of innovation ability would be negatively affected to some degree. In this study, quantitative determination methodology was used in analyzing of the time delay and delayed effect of innovation process. Then the causes of innovation input risks can be revealed and quantified, thus to provide appropriate supports on the prevention of risk in innovation process, the optimal allocation of innovation resources, the improvement of innovation ability and so on.In this study, we collected the comprehensive annual data from 2000 to 2012 of social science and technology activities, and used regression analysis to do a quantitative measurement of delay time. Based on this methodology, we selected the appropriate motivation factors, index elements and transmission elements to create a system dynamics model. Further more, simulation was performed by putting the quantified delay time into delay function and doing quantitative research of delayed effect. Finally, the key influencing factors of innovation delay were identified by combining with sales revenues of new products. In this study, we found that:(1) From the perspective of delay time, compared with governmental funds and loans from financial institutions, the delay time of enterprise funds are the shortest. Therefore, in China’s marketization process, enterprises should be put in the dominant position of innovation inputs, whereas government and financial institutions can play a supplementary role. (2) From the perspective of delayed effect, quantitative analysis of the delayed effect and the delay time can be used to quantify the time and the sunk cost of innovation process, and then to effectively predict the innovation risks. All of these may directly influence the conversion degree from innovation capital and human resources to innovation outputs. On this basis, the quantitative indicators of delay time and delayed effect should be included in the innovation evaluation system, being as an important part of innovation ability evaluation. (3) It is important to shorten the delay time of talent inputs and lower the sunk cost, thereon aiming to improve the input-output efficiency of innovation. Thus, at present, China’s innovation inputs should focus on the talent inputs, to ensure the quality of staff and trigger their passion in innovation researches.Although the present study quantitatively analyzed the delayed effect of innovation inputs by Econometrics and made policy recommendations such as putting enterprises at the dominant position and increasing talent inputs. We still did not reach a clear conclusion about maximum limitation and specific direction of innovation funds and talent inputs. Additionally, even though the delay time of governmental funds is the longest, the government can still provide its assistance to societies. For instance, the government and market should together provide support to the innovation achievements such as quasi-public goods. Meanwhile the industrial generic technology innovation in the enterprise innovation process also needs government to provide funding supports. In our further study, how to control the governmental inputs in order to better support innovation would become the key point.