The government, academia and society are paying more and more attention to scientific research misconduct. Governance of misconduct in scientific research is conducive to the healthy development of the scientific research ecosystem, and improving the punishment mechanism is the main means of governance of misconduct in scientific research.The academic circles have agreed that the punishment intensity for scientific misconduct is relatively weak.It is still relatively lacking and insufficient about the research on the punishment intensity setting and its influencing factors for scientific misconduct.Based on public data, the paper have been collected 213 typical scientific research misconduct cases from 1997 to 2017 and have been constructed seven levels of punishment intensity for scientific research misconduct. With the aid of statistical software, it have been analyzed the influence factors of punishment intensity.The research in this paper finds that the punishment intensity of most cases is between the first and fourth levels, and very few cases exceed the fourth level.Due to the increase in attention, the intensity of punishment in society as a whole has increased, but the intensity of punishment in a single case has not increased over time.The intensity of media attention significantly affects the intensity of punishment; at the same time,the previous notifications of the National Science Foundation of China have gone through a process of increasing publicity: from “someone” of the person’s name and “a certain university” of the institution for academic misconduct to the real-name of the person’s name and “a certain university” of the institution, then come to the real name of the person and the institution. The increasing intensity of notification means that the intensity of punishment is also increasing accordingly.The superposition of scientific misconduct types has a certain impact on the intensity of punishment. There is a significant difference between the punishment intensity of one type of scientific research misconduct and the punishment intensity of the three types of scientific research misconduct.
On this basis, it discusses the distinction between removal measures and punishment measures, corrective measures are not the category of punishment. Therefore, it is necessary to distinguish and refine corrective measures and punishment measures in terms of policy.Then discusses whether the public onlooker effect of academic misconduct can play a role.The institution behavior before and after the public onlooker effect are two sets of logic:the former is to reduce the degree of publicity as much as possible, reduce the impact on the institution’s reputation, and control the handling of the incident within the internal administrative process of the institution;the latter means that since it has been publicly onlooker effect, timely handling is the only way to eliminate adverse effects.And discusses the difficulty of segmented punishment.The implementation of segmented punishment depends on the society’s tolerance for academic misconduct, and the recognition and consensus of social norms.Regarding the problem of scientific research misconduct,it is necessary to get rid of legal centralism and document centralism and carefully review the systemic policy conflict between the current system of over-stimulating the number of papers and combating academic misconduct, so as to achieve cooperative governance pattern of national regulation, academic institution discipline and scholar autonomy.
Leading time becomes most significant when considering the growth of a few large technology companies and digital platforms over the past decade. It is importance for firms absorbing transferred-in technologies quickly to keep up with this uncertain and ever-changing industry environment. By focusing on the speed dimension of absorb capcity theory, this study analyzed the relationship between R&D mode and absorption speed. The relationship was empirically tested by Heckman two-stage regression model, along with data collected from 257 high-tech listed companies in China. The results indicated that there was a positive relationship between collaborative R&D and absorption speed, which is more salient when it comes to the higher generality of the external technology. However, the technological did not moderate the relationship between R&D mode and absorption speed significantly. This study showed some management implications for firms making strategies to cope with the complex and changeable technological environment.
The main feature of industrial intelligence is to reduce the working time of labor and improve the labor productivity. However, a large number of low skilled and repetitive labor will be replaced, and the demand for high skilled and creative labor will increase, with the deepening of "machine for man". All these result in the reallocation of labor, capital and other production factors during industries, which affect industrial structure. Based on the panel data of 2004-2016 in China, this paper calculates the provincial industrial intelligence index, industrial structure optimization and industrial structure rationalization. We analyze the relationship between industrial intelligence and upgrading of industrial structure, and the moderating effect of labor structure and regional heterogeneity, through using the static and dynamic panel regression model. It is found that: (1) Industrial intelligence can promote the upgrading of regional industrial structure, but has a negative impact on industrial structure rationalization; (2) Labor structure plays an important role in the upgrading of industrial structure. The increase of the ratio of high-skilled labor to low-skilled labor and the decrease of the ratio of men to women will promote the positive effect of industrial intelligence on the industrial structure optimization, and relieve the negative impact on industrial structure rationalization; (3) The different effect exists between intelligence artificial and upgrading of industrial structure considering regional heterogeneity. Industrial intelligence has a higher effect on upgrading of industrial structure in the eastern and the central than that of western. The moderating effect of labor force structure is also different. This paper aims at enriching and expanding the relevant research on the upgrading of Chinese industrial structure, and provides new evidence for the evaluation of the effect of industrial intelligence.
Digital technology is the core driving force of the digital economy. Its deep integration with the real economy accelerates the optimization and reconstruction of the production factor system, and gives birth to digital production factors. Taking digital technology as a technology empowering production factors, we expand digital technology to capital-enabling technology and labor-enabling technology. Then we introduce the CES production function to derive the TFP growth formula, which clearly shows the path of digital technology empowerment. Based on the panel data of 27 sub-sectors of China's manufacturing sector from 1990 to 2018, parameter estimation is conducted. It is found that digital technology is the main driving force for the growth of TFP. The annual growth rate of TFP in China’s manufacturing industry is 4.9% while digital technology contributes 4.1%. Digital technology and factor allocation are biased towards capital. The elasticity of substitution of capital to labor under the digital background is 0.763 (complementary relationship). Both the digital technology bias and the element allocation bias have evolved from suppression to promotion. The interactive items between them have evolved from promotion to suppression, showing the characteristics of an inverted U.
With the cross disciplinary digital innovation promoting the emergence of a mass number of emerging industries, and therefore accelerates the revolution of industrial technology, both of emerging and traditional industries. The construction of digital economic system already showed that the development of New Generation of Information Technology industry has significant impacts on other industries and economic development. To measure the industry technology upgrading process scientifically and roundly, multiple dimensional elements and its’ interactions need to be identified firstly. Especially for emerging industries such as New Generation of Information Technology industry which with frequent technology revolution and product iteration, and the technology upgrading process in technology intensive industries is the complex systemic behaviors from the angle of composite system theory. To explore the technology upgrading process, especially the technology upgrading process of New Generation of Information Technology industry, identifying key characteristics and drivers of industry technology upgrading will be of great importance in studying the rapid evolution process of industrial technology. According to this logic chain and research framework, by taking the flat panel display industry as the research example, the composite system model of industry technology upgrading of New Generation of Information Technology industry has been built. The composite system synergy degree has been empirically studied based on multiple dimensional ordered degree indexes of three sub systems (i.e., industry growth sub system, innovative collaboration sub system and industry technology structure sub system) from 2007 to 2017. Empirical data includes patent data from Derwent Innovations Index database and industrial data from the yearbook of information industry and DRCNET Statistical Database System.
Empirical findings of changing trends of ordered degree and synergy degree show the existence of significant periodical, complex and dynamic characteristics of the New Generation of Information Technology industry’s technology upgrading process. During the process of technology upgrading and industry development, and along with the frequent optimization of technology structure and de-centration tread of innovative collaboration, the intensive collaboration between multiple technological fields drives the diversified development of domain technologies. In addition to interactions of sub system behaviors, research findings also show that the upgrading process is also the dynamic transformation from the industry scale growing which driven by production factors to the synergistic growing which driven by interactions of industry scale growth, innovating actors’ collaboration and the optimization of industry technology structure. Multiple dimensions of indexes for measuring the technology upgrading process will be more valuable in studying complex technological evolution of technology intensive industry. In order to rapidly and effectively embed in global industrial and technological competition, more effective innovation policies should be made from the perspective of complex system and based on the whole process of industry technology upgrading. During the process of decision making by governments and firms, some characteristics of the development of emerging industries should also be considered including multi-actors, diversification, openness, and uncertainty. Therefore, research findings will provide theoretical and practical guidance for systemically studying the transition and technology upgrading of New Generation of Information Technology industry and other catching-up industries of China.
Based on a quasi-natural experiment and a difference-in -difference model, the thesis explores the impact of comprehensive innovation reform experimental policy on patent output, and discusses the influence of regional heterogeneity and urban administrative level heterogeneity on policy effect. The results show that the comprehensive innovation reform experimental policy significantly promotes the patent output. Science and technology fiscal expenditure, information infrastructure and urban population significantly promote the patent output. Regional heterogeneity and urban administrative hierarchy heterogeneity affect the policy effect. To be specific, the comprehensive innovation reform experimental policy significantly promotes the patent output of eastern cities and prefecture-level cities. Significant differences exist between eastern and non-eastern cities in the effects of talent reserve and foreign investment.
The evolution of the patent system is an objective historical "freedom"，it has nothing to do with the grand narrative in the philosophy of law, nor is it the construction rationality under instrumentalism that can be directly achieved. This paper attempts to explore how the change of technical paradigm will put forward the reconstruction needs of the unsteady equilibrium of the technology innovation system, and how reconstruction needs are realized in the evolution of the patent system, taking the four industrial revolutions as the central axis. On this basis, suggestions were made for further reform of the Chinese patent system.
