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25 July 2020, Volume 37 Issue 14
    

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    Column of S&T R&D Services for Epidemic Prevention and Control
  • Influencing Factors and Optimizing Strategies for the Collaborative Integration of China's Scientific Research Forces in Response to Major Epidemics
    Zhang Zhihua,Chen Yuxin,Zhao Bo
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 1-7. https://doi.org/10.6049/kjjbydc.ZK202002045
    Abstract ( ) Download PDF ( ) HTML   Knowledge map   Save
    In major epidemics, scientific and technological research and development will play an important role in virus traceability, patient rescue, epidemic prevention and control, and risk management.The effect of collaborative integration is not only related to internal and external factors of scientific research institutions, but also to the process of collaborative interaction between scientific research institutions.Based on the three dimensions of individual, organization, and interaction process, the related influencing factors of the collaborative integration of scientific research forces are analyzed.On this basis, from the aspects of sound coordination and integration system, improvement of emergency management technology support system, cultivation of leading scientific research institutions, application of artificial intelligence technology, linkage with the WHO, and training of emergency management scientific research personnel, etc.An optimization strategy for the coordinated integration of China's scientific research forces in response to major epidemics is proposed.

    Zhang Zhihua,Chen Yuxin,Zhao Bo. Influencing Factors and Optimizing Strategies for the Collaborative Integration of China's Scientific Research Forces in Response to Major Epidemics[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 1-7., doi: 10.6049/kjjbydc.ZK202002045.

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  • Crisis Management based on Science and Technology Perspective and Double-cycle Theory
    Guo Jie,Yang Licheng,Sun Zixu
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 8-13. https://doi.org/10.6049/kjjbydc.ZK2020020120
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    The COVID-19 is a public crisis that has experienced a wide range, great harm and serious impact in recent years. In the field of crisis management, the insufficient level of technological development and application is an important incentive to trigger the crisis. In this paper we constructed a double-cycle curve model of the life cycle and management cycle of an emergency event based on the analysis of the COVID-19 crisis, and then discussed the important role of science and technology in each stage of crisis management. Finnaly we provided some policy recommendations for the scientific and technological development of the emergency industry.

    Guo Jie,Yang Licheng,Sun Zixu. Crisis Management based on Science and Technology Perspective and Double-cycle Theory[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 8-13., doi: 10.6049/kjjbydc.ZK2020020120.

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  • Research on the Integration of Traditional Innovation and Social Innovation and Innovation Transformation in the Context of Major Public Health Events
    Lai Hongbo,Meng Zhe
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 14-20. https://doi.org/10.6049/kjjbydc.ZK202002068
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    The COVID-19 outbreak became a black swan flying out in 2020,which posed severe challenges to the country and caused a major social crisis.Therefore,based on the major public health crisis caused by the new crown epidemic,this paper discusses how local enterprises turn crisis into opportunity,including the integration of traditional innovation and social innovation.On this basis,it further analyzes the characteristics,mechanism and path of the integration of traditional innovation and social innovation,including the case study of 3M and Alibaba social innovation.This paper holds that,taking this epidemic as an opportunity,local enterprises can completely change the past customer-oriented single innovation,turn to the integration with social innovation,so as to promote and realize the innovation transformation and high-quality development of local enterprises.

    Lai Hongbo,Meng Zhe. Research on the Integration of Traditional Innovation and Social Innovation and Innovation Transformation in the Context of Major Public Health Events[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 14-20., doi: 10.6049/kjjbydc.ZK202002068.

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    • Innovation in Science and Technology Management
  • Research on the Effect of Financial Structure on Technological Innovation Efficiency
    Lin Peng,Meng Nana,Chu Xi,Feng Guanlin
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 21-30. https://doi.org/10.6049/kjjbydc.Q201908478
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    This paper takes the stage segmentation of technological innovation as the research basis, Uses the provincial panel data from 2009 to 2018 to construct the transcendental logarithmic stochastic frontier analysis model, and empirically examines the impact of financial structure on the innovation output and the efficiency of technological innovation under different financial development modes in technological R&D and innovation marketing stages.It is found that:in terms of innovation increment, the positive incentive effect of the development of the banking system on innovation output is significantly better than that of the stock market, and the bank-led financial structure plays an important role in supporting and promoting innovation output. In terms of innovation efficiency enhancement, the development of stock market has a particularly significant positive incentive effect on technology innovation efficiency, while the development of banking system has a restraining effect on technology innovation efficiency, resulting in a large degree of technical efficiency loss.The conclusion of this paper indicates that, the increase of innovation output and the improvement of technological innovation efficiency depend on the continuous optimization of financial structure and complement each other's advantages of financial development model.

    Lin Peng,Meng Nana,Chu Xi,Feng Guanlin. Research on the Effect of Financial Structure on Technological Innovation Efficiency[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 21-30., doi: 10.6049/kjjbydc.Q201908478.

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  • Research on The Generating Mechanism of Maker Spirit based on QCA Method
    Cui Xiangmin,Li Zhidong,Chai Chenxing
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 31-38. https://doi.org/10.6049/kjjbydc.2019090216
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    Taking 24 makers from Shanghai, Nanjing and Zhenjiang as samples, the formation mechanism of maker spiritwas explored by using configuration thinking and QCA methodto integrate six influencing factors of endogeneity and exogeneity. The research finds that:①school education is the core and necessary condition for the generation of maker spirit;②maker spirit exists in three effective strategies: educational practice-oriented, interest-oriented and interpersonal relationship-infected, among which educational practice-oriented is the most common strategic combination of creative spirit;③social relation network and subjective cognition have substitution relation in the process of creationist spirit.

    Cui Xiangmin,Li Zhidong,Chai Chenxing. Research on The Generating Mechanism of Maker Spirit based on QCA Method[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 31-38., doi: 10.6049/kjjbydc.2019090216.

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  • Research on Coordination Relationship between National Ocean Innovation Capability and Marine Economy
    Wang Chunjuan,Liu Dahai,Wang Xiqian,Zhao Qian
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 39-46. https://doi.org/10.6049/kjjbydc.Q201908966
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    This paper establishes the evaluation indicators of the two systems of national marine science and technology innovation and marine economic development. Based on the input and output indicators about marine innovation and marine economy, the two sub index of the marine innovation performance and the ocean economic potential are innovatively added to effectively consider the efficiency of marine innovation and the quality and potential of marine economic development. On the basis of the coordination degree model, the mean square error method is used to measure the weights of each indicator in the evaluation index system, and then the coordination degree and coordinated development degree of China's marine innovation and marine economy from 2004 to 2018 are measured. The research results show that the level of marine science and technology innovation and marine economic development in China has been increasing year by year, and the coordination relationship has changed from a moderate maladjusted recession to a good coordinated development. The change of the coordination degree is roughly divided into two stages: marine innovation lags behind marine economy development between 2004 and 2006; from 2007 to 2018the marine innovation drives the marine economy development. On this basis, it puts forward innovative development proposals to increase marine innovation investment and improve marine innovation performance, marine economic development countermeasures to accelerate the adjustment of marine economic structure and industrial upgrading, and countermeasures and suggestions for the coordinating marine innovation and the marine economy development，and so on.

    Wang Chunjuan,Liu Dahai,Wang Xiqian,Zhao Qian. Research on Coordination Relationship between National Ocean Innovation Capability and Marine Economy[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 39-46., doi: 10.6049/kjjbydc.Q201908966.

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    • Regional Scientific Development
  • Functional Division of Urban Agglomeration, Industrial Technology Progress and Pollution
    Lv Kangjuan,Cai Daxia
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 47-55. https://doi.org/10.6049/kjjbydc.2019120937
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    Since 2003, urban agglomerations have rapidly shifted from specializing by sector to functional division in china, whether the optimization of functional division can help improving the environment ?In this paper, we examine the impact of functional division and industrial technological progress on the emission intensity of industrial pollution, using SLX model which only includes spatial lag of independent variables and a panel dataset of Yangtze river delta between 2003 and 2017.Empirical results show that: at the level of urban agglomeration, the relationship between functional division and the emission intensity of industrial pollution is u-shaped;both the enhancement of "structural effect" of functional division and industrial technological progress can significantly reduce the emission intensity of industrial pollution.Within urban agglomeration, both the "spatial spillover effect" of functional division and the "spatial lag effect" of industrial technology progress are conducive to the reduction of environmental pollution in neighboring cities.However, the "technology effect" and "technology spillover effect" of functional division have not effective effect on emission reduction, so the functional division and cooperation between cities within urban agglomeration should be further strengthened.

    Lv Kangjuan,Cai Daxia. Functional Division of Urban Agglomeration, Industrial Technology Progress and Pollution[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 47-55., doi: 10.6049/kjjbydc.2019120937.

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  • Time and Space Evolution and Influencing Factors of Urban Technology Innovation Capability in Guangdong-Hong Kong-Macao Greater Bay Area
    Meng Fei,Lu Zhiguo
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 56-65. https://doi.org/10.6049/kjjbydc.2019110827
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    The paper uses the methods of extreme difference, coefficient of variation, Gini coefficient and ESDA to investigate the the characteristics of spatiotemporal evolution and spatial correlation model of urban technology innovation capability in Guangdong, Hong Kong and Macau, and analyze the influence of cities through the spatial panel Dubin model.The key factors of technological innovation capability, combined with the threshold panel model, further explore the impact of core innovation elements on urban technological innovation capabilities under the threshold effect of economic development level.The results show that: ①the city's technological innovation capability is generally on the rise.After 2014, the growth rate is accelerating, and the technological innovation capability of each city is balanced; ②the city's technological innovation capability is characterized by "central-periphery", and the "central" city is located in the southeastern part of the region.In the eastern bank of the Pearl River Estuary, the spatial correlation model is mainly represented by HH type and LL type; ③human capital and R&D expenditures have significantly promoted the city's technological innovation ability, but the spillover effect of human capital is significantly negative, and the R&D expenditure is negative.The spillover effect is not obvious; ④under the single threshold effect of economic development level, the influence of human capital on urban technological innovation ability rises first and then falls.The promotion effect of R&D investment on urban technological innovation ability is not obvious as the urban economic development level crosses the threshold value.

    Meng Fei,Lu Zhiguo. Time and Space Evolution and Influencing Factors of Urban Technology Innovation Capability in Guangdong-Hong Kong-Macao Greater Bay Area[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 56-65., doi: 10.6049/kjjbydc.2019110827.

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  • Structure Holes and Brokerage Roles of Collaborative Innovation Network in Harbin-Changchun Urban Agglomeration:a Two-dimensional Measurement of Industry-university-research Network and Inter-city Relationship Network based on Patent Data
    Li Xin,Li Baizhou
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 66-75. https://doi.org/10.6049/kjjbydc.2020020753
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    The construction of urban agglomeration and its collaborative innovation network is conducive to the modernization of regional governance system and governance capacity.The purpose of this study is to analyze the strength of collaborative innovation network, define the roles of the dominant position holders, clarify the specific connection form of innovation subjects and inter-city relations in Harbin-Changchun urban agglomeration.The social network analysis method is used to measure the structural holes and brokerage roles based on patent data.The results reveal that the network structure of industry-university-research cooperation is loose.Universities occupy the dominant position in the structural holes and act as the actual brokerage roles of inter-city relations, such as JLU and HIT.Due to the lack of leading innovative enterprises with core resources, the technological marketization ability of enterprises in urban agglomeration cannot meet the technological transformation needs of universities and research institutes.Furthermore, the incentive for universities and research institutes to seek external collaborative innovation cooperation has been formed.The inner inter-city relationship of urban agglomeration is simple, and the peripheral cities are totally or partially subject to Harbin or Changchun.There are many external partners outside the urban agglomeration, and in many cases, the inter-city relationship within and outside the urban agglomeration is established through the gatekeeper or representative played by Harbin or Changchun.

    Li Xin,Li Baizhou. Structure Holes and Brokerage Roles of Collaborative Innovation Network in Harbin-Changchun Urban Agglomeration:a Two-dimensional Measurement of Industry-university-research Network and Inter-city Relationship Network based on Patent Data[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 66-75., doi: 10.6049/kjjbydc.2020020753.

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    • Industrial Technological Progress
  • Research on Measurement and Convergence of Green Total Factor Productivity in Chinese Patent-Intensive Industries
    Yuan Qian,Wu Lihua,Zhang Ping
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 76-85. https://doi.org/10.6049/kjjbydc.2019110066
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    Based on the panel data of patent intensive-industries from 2007 to 2017,the research utilizes GML index model to measure the green total factor productivity of 8 patent-intensive industries and analyses its convergence.The results show that:the overall level of green total factor productivity in patent-intensive industries is relatively high and comparing it with traditional total factor productivity proves that the "Porter Hypothesis" has emerged.The green total factor productivity of patent-intensive industries shows a growth trend on the whole,with the greatest contribution from technological progress.The growth level and dynamic trend of green total factor productivity in different industries are not the same.The internal gap of green total factor productivity in the whole industries,strong patent-intensive industries and weak patent-intensive industries is still large.The whole industries and strong patent-intensive industries tend to converge toward a common steady state and their own steady state,while weak patent-intensive industries only tend to converge toward their own steady state.Industry concentration and industry size have a positive effect on the convergence of the whole industries and weak patent-intensive industries.For strong patent-intensive industries,R&D investment is positively significant.

    Yuan Qian,Wu Lihua,Zhang Ping. Research on Measurement and Convergence of Green Total Factor Productivity in Chinese Patent-Intensive Industries[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 76-85., doi: 10.6049/kjjbydc.2019110066.

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  • The Impact of "Internet +" on the Development of High Quality Industry
    Li Zhenye,Liu Yangcheng,Xu Bin
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 86-93. https://doi.org/10.6049/kjjbydc.Q201908149
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    Based on the static panel model, dynamic panel model and mediator effect model, this paper empirically analyzes the impact of Internet plus on the development of high quality industries from 2008 to 2017. The results show that Internet plus has a significant positive effect on the development of high quality industry at 5% level. According to the results of the mediator model, "Internet plus" can promote technological development, promote the development of high quality industries, and promote the development of high quality industries through the transmission mechanism of green development. The empirical results are still valid through the robustness test of instrumental variable method. Accordingly, it is suggested that we should strengthen the popularization and application of Internet plus, promote market-oriented, enterprise as the main body, and build a collaborative innovation system of industry, university and research institute, promote the development of large-scale industrial clusters, and strengthen the green and sustainable development of industrial enterprises.

    Li Zhenye,Liu Yangcheng,Xu Bin. The Impact of "Internet +" on the Development of High Quality Industry[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 86-93., doi: 10.6049/kjjbydc.Q201908149.

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    • Enterprise Innovation Management
  • Analysis of the Threshold Effect of R&D Investment, Internationalization Degree and Manufacturing Enterprise Value
    Wu Zhiyong,Wang Zeren,Ma Yonghong
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 94-101. https://doi.org/10.6049/kjjbydc.Q201908972
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    Taking China's manufacturing listed companies with foreign sales revenue in 2012-2018 as a sample, the paper empirically analyzes the threshold effect of R&D investment including the current period, the lagging 1 and 2 period and the degree of internationalization on the enterprise value through the panel threshold model.the study finds that there is a non-linear positive correlation between the degree of internationalization and the value of the enterprise, with a single threshold effect;the R&D investment in each period based on the threshold variable－degree of internationalization, has the U-shaped impact on the value of the firm with a significant double threshold effect.The double threshold value of the lag R&D investment of the 1st period and the 2nd period is almost the same; the enterprise age and manpower input in the control variables significantly increase the value of the international operation enterprise, while the enterprise scale and asset-liability ratio negatively affect the enterprise value.The conclusions have important practical significance for leading China's manufacturing enterprises to strengthen technological innovation, promote internationalization process and enhance corporate value under the innovation-driven development strategy.

    Wu Zhiyong,Wang Zeren,Ma Yonghong. Analysis of the Threshold Effect of R&D Investment, Internationalization Degree and Manufacturing Enterprise Value[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 94-101., doi: 10.6049/kjjbydc.Q201908972.

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  • Impact of Entrepreneurial Alertness and Resource Bricolage on Disruptive Innovation
    Wang Jinfu,Huang Tao,Zhang Yingying
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 102-109. https://doi.org/10.6049/kjjbydc.2020030279
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    Disruptive innovation has become an important innovation model due to its advantages such as low resource investment and low competition. However,the key issue of opportunity identification and development has not been effectively resolved. This article introduces the company entrepreneurship theory,selects BYD as the research object,and uses the grounded theory to analyze the case. The research found that: under the auspices of entrepreneurial alertness,company startups perceive and identify disruptive innovation opportunities through the process of scanning,diversifying,refining,and evaluating judgments,and drive enterprises to integrate internal and external resources through resource bricolage,thereby rapidly developing disruptive innovation opportunities. In addition,with the deepening of disruptive innovation,the resource bricolage shows an evolutionary trend from low-level to high-level,from internal resources to social network resources. This article theoretically enriches the relevant research on disruptive innovation,and in practice provides countermeasures and suggestions for enterprises to build a disruptive innovation path.

    Wang Jinfu,Huang Tao,Zhang Yingying. Impact of Entrepreneurial Alertness and Resource Bricolage on Disruptive Innovation[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 102-109., doi: 10.6049/kjjbydc.2020030279.

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  • Empirical Research on Impact of Technology Distance upon R&D Collaboration among Enterprises from Multi-views
    Duan Qingfeng,Feng Zhen
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 110-117. https://doi.org/10.6049/kjjbydc.2018070366
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    There are actually various kinds of differences in exists among enterprises, which may impose significant impact upon relationship embedded in network of R&D collaboration. Meaning of technology distance were discussed overall in two aspects involving magnitude and structure of technology, and some theoretical hypothesis were proposed guided by technology niche theory. Moreover, statistical method of EGRM were used in empirical research based on the patents data in graphene field. Finally, research found that technology distance in dimensions of technological magnitudes measured by index of technology width and technology depth totally have positive impact upon relationship of R&D collaboration, but technology distance in dimensions of technological structure measured by index of technology diversity and technology conflict both have negative impact upon it. Empirical results shown that technology distance in aspect of magnitude would provide the new opportunity for innovative portfolio and extend the potential innovative space, which could offer both sides in R&D collaboration the driving force of innovation. Moreover, in aspect of technology structure, technology approximation would benefit to basis of knowledge communications and technology compatibility with lower transaction cost and higher technology synergism.

    Duan Qingfeng,Feng Zhen. Empirical Research on Impact of Technology Distance upon R&D Collaboration among Enterprises from Multi-views[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 110-117., doi: 10.6049/kjjbydc.2018070366.

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  • Research on the Influence of Enterprise Network Position and Relationship Intensity on Technological Innovation Performance in IUR Cooperation
    Li Mingxing,Su Jialu,Hu Cheng
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 118-124. https://doi.org/10.6049/kjjbydc.Q201908747
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    Taking the Jiangsu-Zhejiang-Shanghai A-share listed company as the research object, the DEA model is used to measure the performance of enterprise technology innovation. From the perspective of network location and network relationship, the empirical test of the enterprise network location and relationship intensity in the industry-university-research (IUR) cooperation on the technological innovation performance of enterprises influences is provided. The research shows that the central position of the network, that is, the degree of centrality, inhibits the improvement of the technological innovation performance of the enterprise to some extent; the enterprise network intermediary position, that is, the intermediate center degree, has a significant positive effect on the technological innovation performance; the network relationship intensity has a significant positive effect on the enterprise technology innovation performance. Finally, the corresponding countermeasures and suggestions are given accordingly.

    Li Mingxing,Su Jialu,Hu Cheng. Research on the Influence of Enterprise Network Position and Relationship Intensity on Technological Innovation Performance in IUR Cooperation[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 118-124., doi: 10.6049/kjjbydc.Q201908747.

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  • The Impacts of Artificial Intelligence on the Productivity of Manufacturing Firms: Is There a Productivity Paradox
    Fan Xiaonan,Meng Fankun,Bao Xiaona,Qu Gang
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 125-134. https://doi.org/10.6049/kjjbydc.Q201908594
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    In the context of a new round of scientific and technological changes and industrial revolution, Artificial Intelligence (AI) has been deeply integrated into various industries and become an important driving force for industrial development. Whether AI can promote the productivity of manufacturing firms has become the key to realize the high-quality development of China's manufacturing industry in the new era. We examine the impacts of AI on the productivity by using the data of Chinese listed manufacturing firms from 2015 to 2017, and build a multiple mediating effect model to analyze the mechanism. The results show that AI improves the productivity of manufacturing firms and market share has a significant negative moderating effect on the relationship between AI and the productivity. Further research of the mechanism shows that AI promotes the productivity through three mediating variables: the quantity of labor, the efficiency of material capital and the output of technological innovation, meanwhile inhibits the productivity through the efficiency of human capital and the input of technological innovation.

    Fan Xiaonan,Meng Fankun,Bao Xiaona,Qu Gang. The Impacts of Artificial Intelligence on the Productivity of Manufacturing Firms: Is There a Productivity Paradox[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 125-134., doi: 10.6049/kjjbydc.Q201908594.

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    • Talent and Education
  • Research on the Relationship between the Salary of High-level Innovative Talents and the Profits of Enterprises
    Liu Jun,Zhang Lei,Chen Mei,He Linzhu
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 135-140. https://doi.org/10.6049/kjjbydc.Q201908786
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    Small and medium-sized technological enterprises are the main force of technological innovation in China, and high-level innovative talents are the "key few resources" of small and medium-sized technological enterprises. Based on the static game theory of incomplete information, this paper constructs the equilibrium model of high-level innovative talents' compensation and corporate profits in small and medium-sized technology-based enterprises. Using the nonlinear multiple regression method and using 111 high-level innovative talents' compensation, corporate profits and other relevant data of small and medium-sized technology-based enterprises, this paper empirically analyzes the relationship between high-level innovative talents' compensation and corporate profits. The results show that the total compensation of high-level innovative talents changes in the same direction as the profits of small and medium-sized technology-based enterprises, and the company's profitability will increase with the increase of high-level innovative talents' compensation; the effect of compensation gap between high-level innovative talents and ordinary employees on the company's profits is significantly related to the growth of the enterprise, and the higher the growth of the enterprise, the higher the compensation gap on the company's profits. The effect is smaller.

    Liu Jun,Zhang Lei,Chen Mei,He Linzhu. Research on the Relationship between the Salary of High-level Innovative Talents and the Profits of Enterprises[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 135-140., doi: 10.6049/kjjbydc.Q201908786.

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  • Understanding "Knowing without Speaking": Influencing Factors and Modes of Employability Voice of New Generation Employees
    Xiang Fei,Liu Xuefang
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 141-150. https://doi.org/10.6049/kjjbydc.Q201908477
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    Exploring the influencing factors of employability voice of new generation employees will be of great benefit to expanding relevant theories and guiding management practice.Under the situation of technology-based SMEs, this paper uses the fsQCA to explore the influencing factors and modes of employability voice of new generation employees.It concludes that employability voice of new generation employees is an organizational facilitative speech act generated by the motivation of employability promotion of those employees.Through the analysis of the antecedent configuration, three configurations of the influencing factors (namely, organizational climate building; professional knowledge and skills upgrading; skills, awards, organizational recognition and interpersonal competence upgrading) are obtained.Finally, the management inspiration and future research directions about how to intervene in this kind of voice in order to promote the innovation of technology-based SMEs are put forward.

    Xiang Fei,Liu Xuefang. Understanding "Knowing without Speaking": Influencing Factors and Modes of Employability Voice of New Generation Employees[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 141-150., doi: 10.6049/kjjbydc.Q201908477.

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    • Review
  • The Latest Progress of Foreign Literature of Entrepreneurial Ecosystem and Future Research Prospects
    Xiang Guopeng,Zeng Chuansheng
    SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(14): 151-160. https://doi.org/10.6049/kjjbydc.2020020726
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    The study of entrepreneurial ecosystem is becoming one of the hot issues in the field of entrepreneurship.In recent years, the development momentum has been growing, and research in this field has been promoted. In order to grasp the latest research frontiers in time, a systematic review of foreign academic ecosystem research literature with a high academic content since 2016 was conducted. Combined with the content of the literature, the latest research progress is comprehensively summarized from the five aspects of entrepreneurial ecosystem components, interrelationships, hierarchical division, dynamic evolution, and system functions. On this basis, future research prospects are proposed on the three aspects of entrepreneurial ecosystem governance, entrepreneurial ecosystem evolution, and entrepreneurial ecosystem functions, and provide a reference for promoting the establishment of entrepreneurial ecosystem theory.

    Xiang Guopeng,Zeng Chuansheng. The Latest Progress of Foreign Literature of Entrepreneurial Ecosystem and Future Research Prospects[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(14): 151-160., doi: 10.6049/kjjbydc.2020020726.

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