With the wide range of influence and academic authority, Bernal Prize is becoming a representative award in the field science of science. In the study of the statistical analysis on the winners and the results of “The John Desmond Bernal Prize”(1981-2015), such phenomena has been revealed, that geographical-concentration-winner, multi-channel- evolution-contents, interdisciplinary research field, generally aging scholar, long period of award-winning and so on. From the phenomena aboved can we more objectively sort out the history and development as well as a variety of features in the formation of the research field science and science, which will greatly contribute to considering the forward extension of the discipline from perspectives of the history of science, the connection of science and technology, along with research strategy., With the wide range of influence and academic authority, Bernal Prize is becoming a representative award in the field science of science. In the study of the statistical analysis on the winners and the results of “The John Desmond Bernal Prize”(1981-2015), such phenomena has been revealed, that geographical-concentration-winner, multi-channel- evolution-contents, interdisciplinary research field, generally aging scholar, long period of award-winning and so on. From the phenomena aboved can we more objectively sort out the history and development as well as a variety of features in the formation of the research field science and science, which will greatly contribute to considering the forward extension of the discipline from perspectives of the history of science, the connection of science and technology, along with research strategy.
Whether it is "Science 2.0" or "Science II", scientists believe that science is undergoing a structural revolution. Karl Miller, a professor of Steinbeis Transfer Center New Cybernetics in Vienna, proposed Second Order Science theory unifying science based on the second-order control theory and the cognitive point of view of biology on how individuals construct a "knowledge reality" , through introducing the observer's perspective into scientific research and depending on the reflection and re-entry to first-order science, which becomes a new trend of the research of philosophy of science.
Natural history was considered as a classless scientific practice, because everyone from every class seemed have the access to it. However, people from different classes practiced natural history in quite different ways and what they can achieve was also quite different, too. Along with politeness, noble natural history was supported by wealth, social position and power. It greatly influenced national strategies, academia and popular culture. Royal passion on natural history helped with its popularity in public. Royal society led by Joseph Banks took natural history as the most important part of the society and integrated it into imperialism. Curious natural collections and luxury hand-colored books witnessed the high materialization of natural knowledge. There was no equality among different classes in their interaction of natural history practices, either. Moreover, the naming of species even marked the power of knowledge. Therefore, classless natural history was just an illusion. It was impossible to ignore the class character and noble feature of natural history.
Through the establishment of long-term equilibrium equation, Error Correction Model (ECM), Vector Error Correction Model (VEC) and Bayesian VAR Model, the paper analyzed the influence of different sources S&T investment to GDP of China, investigated the dynamic relationship between these sources. Through the contrast with the same model of the United States and Japan’s R&D data, the study reflected all kinds of S&T investment’s actual contribution to GDP and the influence between each investment. The model also rendered and verified the problems in S&T investment of China, that should be pay attention and settled.
Whether the high-speed growth of patent calculated knowledge capital really have the potential to boost long-run economic growth and whether it has significant and positive effect on real economic growth are two main problems concerned by scholars and discussed in this paper. Based on assumptions of knowledge production function promoted by Romer and Jones in endogenous growth theory, this paper estimates parameters of the knowledge production function using Chinese knowledge capital calculated by granted patents in 30 provinces during 1996 and 2014. We find that the endogenous accumulation of knowledge capital has not been strong enough to breakthrough the long-run economic growth rate constrains and support Chinese economy to grow at such high speed in the long run. In addition, this paper estimates the actual promotion effect of knowledge capital on real GDP growth using fixed-effect semi-parametric method in different time periods. We find that with patent system perfecting knowledge capital will effectively boost economic growth. And the high speed growth of knowledge capital has limited promotion effect. Once the knowledge capital grow too fast for the patent transformation capacity, knowledge capital do little to promote economic growth. Knowledge capital calculated by invention patents, which represent high quality part of knowledge set, appears to boost economic growth more significantly than patents in the whole. We suggest that, the intellectual property policies should emphasis more on the quality rather than the quantity of patents to reinforce the effect of knowledge endogenous accumulation. The government should reduce intervention policy which focus on short-term patent quantity growth and emphasis more on market resource allocation mechanism. We should highlight the importance of patents commercialization and industrialization by formulating the co-operation innovation network.
According to the status of China's industrial technology innovation resource allocation under the new normal, this article constructs evaluation index system from four aspects based on the perspective of value chain, including the R&D investment, non R&D investment, output of scientific and technological achievements and output of industrial achievements. Using the projection pursuit model coupled with maximum entropy, Theil index and exploratory spatial data analysis method, it conducts an empirical study about the regional difference, cause of difference and temporal and spatial pattern change based on the industrial panel data of 30 provincial regions of China in 2011-2014. The results show that, on the one hand, China's industrial technology innovation resource allocation continued to present an unbalanced situation——East High and West low, the differences inside one region and between regions influence the total roughly and the difference in eastern region plays a particularly prominent role among the above differences; on the other hand, China's industrial technology innovation resource allocation performs as the positive spatial autocorrelation in general, but the correlation has the stage characteristics of weakness-enhancement-weakness and the whole high value clustering increases gradually over time; the provincial industrial technology innovation resource allocation has different clustering models, the clustering state in local area exists spatial-temporal evolution, but the overall spatial distribution pattern has not fundamentally changed over time.
Industry convergence causes the value chain of different industries to be deconstructed and reorganized, and the modes and its ability of value-added are also changed. This paper starts from the interactive convergence of different types of industries: convergence among traditional industries, convergence between traditional industries and emerging industries, convergence among emerging industries. It explores the transition of core value area of the three models after certain convergence among industries respectively and comparatively. This study reveals that the industrial value can transfer or increase after convergence, and will differ under various convergence models. The conclusion might complement the future study of industry convergence theory and regional value chain theory.
Based on the dynamic perspective of labour productivity growth mechanism which is from the capital threshold to technical promotion, by the analysis of provincial and regional disparity, and the comparative research on OECD. The study explores the influence of technology efficiency, technology progress and capital accumulation on the growth of labor productivity in 1978-2014 by using three-stage DEA method and kernel density estimation method, measuring and decomposing the growth of labor productivity. The study shows that: (1) There is double threshold in capital scale, both inadequate and excessive capital investment limited the contribution of capital accumulation efficiency to labour productivity growth, and then the transformation from size bottlenecks to technologies is necessary. (2) With the improvement of capital accumulation, the key to narrow regional disparity is technological progress under the capital threshold. The distribution of regional disparity to labor productivity which is caused by capital threshold and technical transformation presents a M type dynamic evolution trend. (3)Technical progress is the reason for OECD to achieve steady increase in labor productivity at a high level of capital accumulation. Technology promotions an important way for Chinese labour productivity growth to cross capital threshold.
The multiple interaction and resource cooperation among the university, government and industry can facilitate the development of the university entrepreneurial talent training program. Our research, based on the triple helix theory, intends to construct a conceptual model in which four factors influence one another like government – industry – university participation, relevant entrepreneurial competence of teachers and students, entrepreneurial talent training performance, and government – industry – university cooperation. Supposing the relevant entrepreneurial competence of teachers and students as the meditation variable, and the government – industry – university cooperation as the moderation variable, we testify our research through extensive questionnaires and data analysis and come to the main conclusions as below. First of all, the government – industry – university participation reveals a distinctive positive effect on the entrepreneurial talent training performance. Next, the relevant entrepreneurial competence of teachers and students shows a partial meditation between the government – industry – university participation and the entrepreneurial talent training performance. Thirdly, the government – industry – university cooperation has a notably positive moderation on the government or the university participation and the entrepreneurial talent training performance. It is expected the theoretical analysis and empirical methodology in this research can broaden the triple helix theory and also deepen the scope of the university entrepreneurial talent training program.
Improving the success rate of entrepreneurial activities in colleges and universities is an important way to promote national scientific and technological innovation. However, the success rate of science and technology entrepreneurship is not high in China and it’s easy to fall into the "Death Valley" in 2-3 years ". The nature of this phenomenon which is very frequently maybe are lacking of awareness of the Academic Entrepreneurship objective laws and understanding of scientific research personnel in the entrepreneurial process, therefore, this research constructed a theoretical model of academic entrepreneurship creation process based on grounded theory.
According to Aghion(2005), enterprises’ cyclic structure of short and long term investment is different. Based on his theory, we build a theoretical model under imperfect capital market in which government subsides ease financing constraints and thus affect the cyclicity of R&D investment. Using panel data of 1580 listed manufacturing enterprises during the period 2007~2014, we conclude that: (1) There exist universal financing constraints in manufacturing enterprises in China, and state-owned enterprises suffer more financing constraints than non-state-owned enterprises; (2) Due to imperfection of capital market and external financing constraints, enterprises' R&D investment shows procyclicaity when we use state-owned enterprises, non-state-owned enterprises and all samples, and the procyclicality of R&D investment is more obvious in non-state-owned enterprises than in state-owned enterprises; (3) Government subsidies can alleviate financing constraints and the procyclicality of R&D investment to a certain extent. The effect of government subsidies is more obvious on non-state-owned enterprises than on state-owned enterprises.
Using Chinese listed manufacturing firms' data, this paper empirically examines the incentive effect of R&D additional deduction policy on firm’s R&D investments and verifies whether the incentive effect is related with firm heterogeneity such as market competition environment, firm size, firm life cycle stage and industry characteristics. The results are as follows: (1) Additional deduction policy has a positive effect on firm R&D input. (2)The incentive effect doses vary across firm life cycles, industry characteristics and. It’s better for mature firms and low-tech enterprises and the higher for the marketization degree, the worse is the inventive effect.
Based on Schumpeter's innovation cycle theory to explain economic growth cycle,it regionally defines the economic growth driven by scientific and technological innovation volatility and cyclical concept, and construct the measurement tools and models,and use Chinese scientific and technological innovation and macro-economic climate index to synthesize Chinese economic growth driven by scientific and technological innovation index, and use this index to measure the short and medium cycle volatility characteristics of Chinese economic growth driven by scientific and technological innovation.The research results indicates:Chinese economic growth driven by scientific and technological innovation volatility is not a random fluctuation, but a certain cyclical fluctuation;The cyclical duration, amplitude, frequency, peak, trough, and other indicators are influenced by external environmental changes, showing the unequal intervals , not repeating,, asymmetric features;The effect of volatility shocks from changes in the external environment are temporary and small, and the economic growth driven by technological innovation in the long-term trend is steady;In the monitoring period, the overall trend of Chinese economic growth driven by scientific and technological innovation fluctuations is stable, but the actual level needs to be improved quickly, and the scientific and technological innovation driving force need to be enhanced urgently.
The intellectual property pledge loan to innovative enterprise plays an important role in the development of innovative enterprises and financial products innovation. One important reason for the slow development of innovative enterprises intellectual property pledge loan in practice is that the commercial banks face huge risks and is lack of objective method to assess the risk. From commercial banks ' perspective this paper explores assessment factors system of innovation enterprise intellectual property pledge loan, and builds a commercial bank scoring table to determine the intellectual property pledge loan risk of commercial bank and its weight in order to increase the objective of innovation enterprise intellectual property pledge loan risk assessment of commercial banks.This paper provides a theoretical reference for defusing the problem of "innovative enterprise credit rationing dilemma", and a realistic basis for improving intellectual property pledge loan policy.
The theoretical and practical conflicts concerning the relationship between debt financing and innovation performance have existed for a long time. This paper has introduced governance duality theory and enterprises’ life cycle theory as theory explanation, and tested the impact of both relational and contractual governance upon innovation performance around enterprises’ life cycle based on the study of the features and mechanisms of both relational governance and contractual governance of bank debt financing and the innovation risk distribution around enterprises’ life cycle as well. Is has been found out that driven by innovation premium, banks’ relational governance possesses innovation tolerance feature and can advance the constancy of innovation input. While the contractual governance possesses innovation conservation feature, and can help bank control innovation risk. Since the environmental risk brought by innovation activity is distributed in both growing and transforming periods and the moral risk is mainly distributed in the latter one, the contractual governance can boost innovation performance of corporations in growing period, while the boost effect of relational governance has shown in mature period. However, when comes to the transforming period, both of them have shown restraining effect towards innovation performance.
Use Artificial Neural Network and Ordinary Least Squares regression method to explore the effect of geographic proximity and cognitive proximity effects in the synthetic knowledge based and analytical knowledge based industry innovation in the national and the three regional levels. We find that geographical proximity effect on the synthetic knowledge based industrial innovation is significantly accelerated with the type of half inverted "U", and the influence degree is higher than the weak promotion effect of cognitive proximity. Geographical proximity effect on the analytical knowledge based industrial innovation is like narrow inverted "U", the influence degree is lower than the cognitive proximity effect. Geographical proximity effects are over saturated in the eastern region. Geographical proximity and cognitive proximity effects are positive in synthetic knowledge based industries but showing inverted "U" in analytical knowledge based industries in the central region. Cognitive proximity effects need to be more cultivated in both synthetic and analytical knowledge based industries in the western region.
