This paper analyzes the interaction of science, technology and economic growth use papers as science variable substitution and patents as technology variable substitution based on panel data, panel vector error correction, Granger causality. The results show the mechanism of science to economic growth differs with that of technology. The contribution of technology to economic growth is familiar but that of science is weak. Economic growth is the basic power of science and technology which pushes science and technology a lot. The interaction relation of science and technology is visible and forms virtuous cycle. “Science and technology” only means technology in many occasions. This paper discusses the input structure of science and technology at last.
The industrial revolution witnessed the rise of the firms; in return the growing firms improved the process of industrial revolution. There must be a kind of generalized causal relationship in the phenomenon emerged in secession. The new complexity science provides a useful way to explain this complex phenomenon. This paper tries to use "coupling theory" explain the origin of the firm, scale and characteristics. The firm is a kind of economic organization in which capital and labor was coupled up by technology, the size of the firm depends on the control variable (technology) of the coupling system. The technology is the hub of a firm and the most important component of the core competitiveness of firm. The explanation of origin of firm by way of coupling theory is novel and powerful.
Knowledge collaboration is a new stage of knowledge management and collaborative management. The existing literature shows that there is the diversity in cognition of concept, connotation, key elements and the operation systems of knowledge collaboration. Based on the literatures related knowledge collaboration, and from three dimensions of concept connotation, key elements and the operation systems, this paper summarizes the typical points of view, and puts forward the basic ideas and theoretical framework of knowledge collaboration, in order to depict the basic essential views of knowledge collaboration and to outline its developing situation. Finally, paper points out that it need strengthen the study on basic theory and ideological system of knowledge collaboration in the further research activity.
This paper was based on data of China Civic Scientific literacy Survey in 2010, using confirmatory factor analysis(CFA) to extract factors of Interest(public interests in S&T),Engagement(public engagement of S&T ),Information(the information sources of S&T). We built the model of civic scientific literacy and its impact factors of China via structural equation modeling (SEM), which revealed the features of how these influential factors affected the Chinese citizens’ scientific literacy. Reliability and validity of the model were also tested. A comparative analysis was made through the American researchers’ similar study, it summarized different social contexts in US and China results in different influential factors which affected civic scientific literacy. It had made an attentive effort to improve the level of Chinese citizen’s scientific literacy and Chinese public understanding of science.
this article introduces the concept of co-evolution based on evolution theory, and reviews the development history of co-evolution theory. The relationship between technology and institution is co-evolutionary, neither unidirectional decided, nor simple bidirectional decided. The innovation case in industry revolution is used to discuss the co-evolution process and mechanism of technology and institution during industry developing, economy development to some extent is the result of co-evolution of technology and institution, and some policy implication is given in conclusion.
As an important part of the transformation of the pattern of economic development, a fundamental approach of the upgrading of traditional industries is to utilize those hi-tech achievements, i.e. the hi-tech transformation of traditional industries. The mainstream logic on this topic is to reform traditional industries by hi-tech ones, especially by digitalized equipment. This research discusses technical change in vehicle diesel engine in the past four decades. It shows that it is indigenous product development in traditional industries that results in endogenic and gradual technical change and thus is more effective than equipment upgrading. Product development therefore is confirmed as the main approach and key factor in the transformation. In the final part the paper summarizes the situation and related policy insights of the transformation based on product development.
With the in-depth development of technical revolution and changes in the characteristics and the nature of the technical standards, comprehensive standards characterized by modern technology standards system are becoming increasing important. On the basis of the analytical on the development trend and characteristics of the standards in the era characterized by barriers of technical standards , this paper elaborates empirical analysis on the coordinated development of technical innovation and technical standards at home and abroad, and proposes to promote the comprehensive standardization as a breakthrough technology standard system, consequently sums policies and measures to achieve strategic pattern of coordinating development of technical innovation and technical standards.
The technological similarity among enterprises is an important content of enterprises’ technological intelligence analysis. Approach and process for technological similarity analysis for enterprises based on patent coupling is raised, in order to supply enterprises with effective decision-making information and help enterprises to search for technology competitive and cooperative objects worldwide. First, this paper compares some relate approaches in previous studies and points out that patent coupling analysis is a more accurate and real-time approach for reflecting technological similarity among enterprises. Secondly, the paper improves the method for calculating the coupling strength of the paired enterprises based on elaborating the principles of patent coupling analysis, in order to effectively distinguish the difference of coupling strength among several coupling pairs. Thirdly, the paper construct a visualization and application process framework for analyzing technological similarity among enterprises, through applying correlation analysis and multiple-dimension scaling based on the coupling data. Finally, this paper reveal the technological similarity among the primary organizations in the field of flat panel display, it further demonstrates the visual analysis and application process of enterprises’ technological similarity analysis based on patent coupling and can provide a guide for enterprises’ technology intelligence analysis.
Abstract: What’s the China's current R&D intensity level compared with other country? If we want to further enhance the China’ R&D development level, should we increase government investment or business investment? Are the China’s basic research, applied research and development of three character of work having the same growing speed? Who causes China’s basic research intensity lower than other countries, the government or the business? In the future, what should the Chinese government and business enterprises try to do, in order to adjust the investment structure and investment intensity of the three different character of work, and further promote Chinese research and development ability? All these questions are this paper attempts to answer.
Based on the Tran slog stochastic frontier model, this paper makes empirical study about environmental regulation intensity’s affect on China industrial R&D innovation efficiency as well as its trans-industrial difference during the years between 2004 and 2010. The result indicates that, the heterogeneity exists in China industrial R&D innovation efficiency. Although, to a certain extent, the environmental regulation intensity promotes the industrial R&D innovation efficiency, the inverted "U" type relationship appears between these two sides. That is to say, the influence of environmental regulation intensity on China industrial R&D innovation efficiency is relatively limited. When environmental regulation intensity exceeds a certain level, it will not be conductive to the increase of industrial R&D innovation efficiency. The influence of the former on the latter one presents the eminent industry difference. Among those industries that are technology-intensive, less polluted, with high R&D intensity, the environmental regulation will promote the R & D innovation efficiency more significantly.
In order to unveil the black box of management decision ‘having knowledge transfer activities of technology alliance but lacking of the effectiveness’, a theoretical model of influence factors of knowledge transfer effectiveness in technology alliance was constructed from the three layers including knowledge、 allied enterprise and circumstances in the basis of previous studies. Data collected from a questionnaire survey of 201 domestic enterprises were validated by using SPSS16.0 software, and then hypothesis was further verified by using LISEREL8.70 software. The results show that relevance of basic knowledge, difference of professional knowledge, knowledge transfer ability of sender, knowledge absorption ability of absorber, and trust among allied enterprises have a significant positive influence on knowledge transfer effectiveness; The knowledge transfer effectiveness is not directly affected by trust among allied enterprise but indirectly impaired by acting on promise.
Since the introduction of absorptive capacity as an important construct to understand firms’ learning behavior, studies in this field have undergone a gradual transformation in the last three years. Absorptive capacity has been increasingly viewed as a dynamic competency that evolves over time with environment. From a dynamic competency view of learning, this article aims to discover whether firms restructure their absorptive capacity to improve innovation and financial performance under different knowledge environments. Data from a survey conducted in 113 firms confirms the above hypothesis. It contributes to the literature by confirming empirically that firms need the synergies from absorptive capacity subsets to achieve optimal performance. Besides, this article further details what combinations of absorptive capacity subsets firms use as the tacitness of their knowledge environment varies. This lends important insights into how firms survive the tension between resource constraints and learning. Business practitioners can also use those findings to optimize their resource investments and improve learning efficiency.
Based on principle analysis and research hypothesis, construct a index system to estimate on knowledge elements in conversion of agricultural technological production. From the result of statistics it approves effective, and then we gauge the correlation coefficient through the empirical data processing. This research fruit not only provide a new prospective, but also provide a theoretical model and a maneuverable method to understand and improve conversion efficiency of agricultural technological production, and laying a foundation for studying conversion of agricultural technological production from qualitative analysis to quantitative analysis, thus it maybe can explore a new way to rectify agricultural technological production popularization system and courses.
Use panel data sets collected from five high-tech industries in Chinese 31 provinces through year 1995-2010, this study examines effects of geographical proximity, technological proximity and combined proximity on inter-provincial knowledge spillovers respectively by spatial panel data analysis. The empirical results indicate that, first, estimations of spatial panel data analysis is more precise than that of common panel data analysis. Second, R&D capital contributes more than R&D labor on knowledge production. Third, whether under geographical proximity or technological proximity, the presence of Chinese inter-provincial knowledge spillovers in high-tech industries is much evident, in which technological proximity has a little more effects, but the effects of combined proximity is not sufficient as presumed. The estimation varies with different model specifications and its implications are discussed.
This paper constructs an analysis framework of time-filed, and analyzes the distribution structure evolution of the U.S. technological innovation base on the patent data of 1963-2008. Firstly, the result shows that the distribution structure of the U.S. technological innovation fields gradually concentrates on just a few technology fields from 1963 to 2008 with the approach of rank-frequency and concentration ratio. In recent years, it always maintains in the “5-55” pattern. That is to say, the patents of top 5 technology fields which have the most utility patents account for about 55% of all the utility patents in the U.S.. Then, according to the total patents and the relative growth rate of each technology innovation field, we divide them into 4 development patterns which are leading-growth, emerging-growth, leading-maturity and germinative (recession)-sluggish. The result of CV (coefficient of variation) indicates that leading-growth and emerging-growth patterns develop unstably and the leading-maturity pattern develops relatively stably.
Abstrct: Network integrating beyond boundaries is a critical path of capability upgrading in the context of globalization.The co-evolution theory which emerged gradually in recent years has been agroundbreaking research and tools for the analysis of network integrating and capability upgrading. Through a longitudinal case study of the development of a large clustered firm in Zhejiang province, the paper explores that: (1) The upgrading of innovation capabilities is the interactive dynamic evolution of incremental innovation capability and radical innovation capability. (2) The dynamic transformation of ambidextrous capabilities feedbacks to the network morphologica is the breakthrough of network boundaries, and the synergistic integration of the internal and external networks of multi-dimensional boundaries. (3)Network integration beyond boundaries requires ambidextrous capabilities upgrading to adapt to the changes of network structure and relationship.
Network function depends on the structure of the network, the network structure is determined by the individual behavior on the network, and therefore the optimization of the network functions shall proceed from the optimization of individual behavior on the network .In this paper ,the Correlation analysis between the each two-sequence data was made with the individual reading time series data,the sequence data of attention to other users and participate in the group's data from Douban.com communities,and the resulting was the behavior process that individual embedded network. Through the comparison of the innovative individual group and the individuals group without innovation capability for behavior process,individual network embedness was found in the individual of innovation capability,but was not found in the individual of non innovation capability.The findings show that individual network embedded behavior can be optimized by the way of that the innovative individual embedded network.And As for the research methods, throughout the course of the study reflects the research paradigm which respect for data,respect for the process of grounded theory,This is a pioneering attempt to standardize the process of network research and optimize network structure,improved network functionality.
This research adopted the idea of multiple-case study combined with grounded theory coding method. After theoretical sampling of representative enterprises, we built an exploratory incentive mechanism mode of innovation policy to innovation input on perspective of innovation stakeholders. The results showed as flowing: By influencing on ”interests – power” demand of shareholders, competitors, executive officers, employees and partners, supply policy has an effect on the innovation investment behavior of these stakeholders. While environmental policy took an influence on shareholders’ and competitors’ innovation investment behavior via impacting their “interests – power” demand. At last, demand policy affected shareholders’, competitors’ and partners’ innovation investment behavior by means of influencing their “interests – power” demand. This research introduced stakeholder theory into the study of innovation policy motivating mechanism. The main innovative points of this research are research perspective, sample selection, research methods and integration of existing research. Finally, the possible limitations were expounded.
