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Impacts of Entrepreneurial Network Structure on Absorptive Capacity in Effective Trust Context

Sun Wei,Hou Xilin

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 1-8. https://doi.org/10.6049/kjjbydc.2019050241

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An effective way to overcome the liability of newness and obtain various resources for the new ventures is to establish and develop entrepreneurial network.Based on the theories of social network and absorptive capacity,and combined the background of social relations in China,the theoretical model of entrepreneurial network structure,effective trust and absorptive capacity is constructed.It is found that network size,network intensity and network diversity all have a significantpositive impact on absorptive capacity,effective trust has a significant positive impact on absorptive capacity,and effective trust positively moderates the relationship between network intensity and absorptive capacity,and positively moderates the relationship between network diversity and absorptive capacity.The results of this study can provide some implications for entrepreneurs to adjust their entrepreneurial activities from the aspects of network structure and relationship trust so as to improve the ventures′ absorptive capacity.

Sun Wei,Hou Xilin. Impacts of Entrepreneurial Network Structure on Absorptive Capacity in Effective Trust Context[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 1-8., doi: 10.6049/kjjbydc.2019050241.

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An Empirical Study of the Impact of CVC Investment Model on the Performance of Large Companies' Technological Innovation

Zeng Wei,Shen Yaning,Tang Yu,Yang Huanhuan

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 9-15. https://doi.org/10.6049/kjjbydc.2019060547

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Corporate Venture Capital (CVC) usually occurs in industries with rapid technological changes and fierce competition.Large companies use CVC to acquire new technologies, open up new markets, identify new opportunities and develop new business relationships, and realize big company technology.Innovative performance strategy goals also bring financial performance.Due to the motivation of CVC investment, organizer background and mechanism, the different investment modes formed in CVC investment practice affect the technological innovation performance of large companies to varying degrees.At present, the research on venture capital of large companies at home and abroad rarely involves From this perspective, it is of great theoretical and practical significance to study the impact of CVC investment model on technological innovation performance.This paper proposes research hypotheses based on the impact of CVC investment model on technological innovation performance, and uses T test and T-test and 918 CVC investment events involving 12 active CVC listed companies in Tencent and Alibaba.The one-way ANOVA method empirically studies the impact of CVC investment model on technological innovation performance.The empirical results show that: (1) There are significant differences in the impact of different CVC investment models on the technological innovation performance of large companies; (2) The impact of the alliance model on technological innovation input and output is significantly better than the affiliated venture capital and entrusted investment models.(3) Different CVC investment model selection proposals are proposed for large companies with different capital, experience and risk tolerance.

Zeng Wei,Shen Yaning,Tang Yu,Yang Huanhuan. An Empirical Study of the Impact of CVC Investment Model on the Performance of Large Companies' Technological Innovation[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 9-15., doi: 10.6049/kjjbydc.2019060547.

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The Impact of Customer Participation in Virtual Community on New Product Development Performance

Zhang Jie,Cai Hong

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 16-25. https://doi.org/10.6049/kjjbydc.2019030501

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Based on the theory of customer participation and virtual social capital, combined with the characteristics of virtual communities, from three different dimensions, the moderating effects of virtual social capital between customer participation in virtual communities and performance of new product development were studied.The research results show that structural capital positively moderates the relationship between interactive information providing and novelty of new products, the cognitive capital negatively moderates the relationship between online participation in the creation and novelty of new products, and the relational capital positively moderates the relationship between online participation in the creation and launch speed of new products.The other has no significant moderating effects.This research can not only enrich the theory of customer participation and its effects on the performance of new product development, but also can provide guidance for Chinese enterprises to implement interactive products innovation under the virtual community environment.

Zhang Jie,Cai Hong. The Impact of Customer Participation in Virtual Community on New Product Development Performance[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 16-25., doi: 10.6049/kjjbydc.2019030501.

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Technological Innovation and Industrial Structure Upgrading of the Yangtze River Economic Belt

Zhang Zhidong,Liao Changwen

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 26-34. https://doi.org/10.6049/kjjbydc.Q201908133

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Technological innovation is the internal driving force to promote the transformation and upgrading of industrial structure.Based on the panel data of prefecture-level cities in the Yangtze river economic belt from 2007 to 2017, this paper adopts the panel Tobit regression method and threshold effect analysis method to investigate the influence mechanism of regional technology innovation on industrial structure upgrading under the effect of marketization regulation.The results show that regional technological innovation can effectively promote the rationalization and development of industrial structure, and the driving force becomes stronger and more significant after the introduction of marketization.Further research shows that such a regulating effect also shows threshold effect in the rationalization of industrial structure.In the sectional analysis, the regulating effect is relatively strong in the upstream and mid-stream cities, but relatively weak in the downstream cities.Therefore, it is suggested that regional development heterogeneity should be emphasized and an optimal market environment should be constructed to support regional innovation's role in promoting industrial structure transformation and upgrading.

Zhang Zhidong,Liao Changwen. Technological Innovation and Industrial Structure Upgrading of the Yangtze River Economic Belt[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 26-34., doi: 10.6049/kjjbydc.Q201908133.

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An Analysis on the Development Environment of Science and Technology Innovation Talents in Shenzhen Based on Principal Component Analysis

Cui Hongyi,Pan Mengqi,Zhang Chao

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 35-42. https://doi.org/10.6049/kjjbydc.2019080296

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Talent is the core strength for achieving high-quality development, the talent environment influences the flow of talents and the ability to innovate.This paper takes Shenzhen Science and Technology Talents Environment as the research object, and selects 6 secondary indicators such as regional economic environment, cultural and educational environment, employment and entrepreneurship environment, living security environment, science and technology support environment, results transformation environment, and 34 three-level indicators to construct an environmental assessment system for scientific and technological innovation talents, and use principal component analysis method to analyze and evaluate the changing laws and factor characteristics of Shenzhen's scientific and technological innovation talents environment.The study finds that the talent development environment has shown a process of improvement, rapid improvement and deep improvement; in this process, the economic development factor is the most obvious improvement, the adjustment of the housing security factor is the weakest, and other factors have a positive effect; the factors have the best fitting effect in 2012, and then the mutual differences are gradually expanding.Finally, based on the empirical research and the reality of the country's construction of the Guangdong-Hong Kong-Macao Greater Bay Area, the relevant policies and recommendations for further improvement are proposed.

Cui Hongyi,Pan Mengqi,Zhang Chao. An Analysis on the Development Environment of Science and Technology Innovation Talents in Shenzhen Based on Principal Component Analysis[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 35-42., doi: 10.6049/kjjbydc.2019080296.

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Research on Influencing Factors of Technology Innovation Efficiency of High-tech Industry in China

Li Shengnan,Fan Decheng

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 43-51. https://doi.org/10.6049/kjjbydc.2019050041

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It is of great significance to systematically identify the influencing factors of technology innovation efficiency of high-tech industry and clarify the interaction between influencing factors for formulating strategies to improve the technology innovation efficiency of high-tech industry.By using the method of document coding analysis, this paper codes and refines relevant literatures on the influencing factors of technology innovation efficiency in China's high-tech industry from CNKI during 2000-2018.Then this paper constructs a comprehensive research framework of influencing factors.The results show that the influencing factors of technology innovation efficiency of high-tech industry mainly include seven themes: quality of innovation factors, industrial organization factors, industrial agglomeration level, industrial openness, industrial innovation orientation, technological factors and environmental factors.The interaction among the influencing factors is complex, which affect the technology innovation efficiency of high-tech industries.Finally, according to the conclusions of the study, the paper puts forward relevant strategies to promote the efficiency of technology innovation of high-tech industries.

Li Shengnan,Fan Decheng. Research on Influencing Factors of Technology Innovation Efficiency of High-tech Industry in China[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 43-51., doi: 10.6049/kjjbydc.2019050041.

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The Impact of Innovation Elements on Innovation Performance under Different Levels of Economic Growth and the Policy Implications

Li Jia,Wang Lili,Wang Huanming

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 52-58. https://doi.org/10.6049/kjjbydc.2019090166

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In this study, the new-generation information technology industry was selected as the subject.From the perspective of different levels of economic growth, the improved Griliches-Jaffe knowledge production function model was adopted.The panel data regression analysis method was used, and an empirical study was conducted based on the statistical data of electronic and communication equipment manufacturing industry in China Statistics Yearbook on High Technology Industry (2007-2017) to explore the relationship between innovation elements input and innovation performance.The results showed that for the new-generation information technology industry, there were differences in the impact of the same innovation elements on innovation performance in regions with different levels of economic growth especially in the effect of technology input factors, suggesting that it is inefficient to use the same innovation element to promote industrial innovation development in regions with different levels of economic development.Targeted distribution of innovation elements in regions with different levels of economic growth is particularly critical to achieve the maximum efficiency of innovation elements and promote the layout and development of strategic emerging industries.The corresponding policy implications and suggestions were also provided in this paper.

Li Jia,Wang Lili,Wang Huanming. The Impact of Innovation Elements on Innovation Performance under Different Levels of Economic Growth and the Policy Implications[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 52-58., doi: 10.6049/kjjbydc.2019090166.

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High-tech Industry Green Technology Innovation Efficiency and its Scale Quality Threshold Effect

Zhang Feng,Ren Shijia,Yin Xiuqing

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 59-68. https://doi.org/10.6049/kjjbydc.2019080079

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Improving the ability of green technology innovation is an important way to promote the high-quality development of the industry in the new era.Based on panel data of 28 provinces nationwide from 2008 to 2017 and stochastic frontier function, environmental variables such as government support intensity, regional economic development level and technology level were introduced into the construction of three-stage combined efficiency measurement model for green innovation in high-tech industry.Moreover, the panel threshold model was constructed to empirically analyze the impact mechanism of enterprise scale quality on its green technology innovation efficiency.Results showed that, the strength of government support, regional economic development level and technological level had shown significant heterogeneity impact on the efficiency of green technology innovation in high-tech industries.After eliminating the statistical bias caused by environmental factors, the efficiency of green technology innovation in domestic high-tech industries had steadily improved during the measurement period, but it still had a large room for improvement.The high-tech industry green technology innovation efficiency had obvious geographical spatial differences, among which the eastern region was the highest, and the central and western regions were relatively low.Furthermore, the scale quality of high-tech industrial enterprises had a double threshold effect on the efficiency of green technology innovation, and the industrial agglomeration, market environment and labor quality had a significant positive effect on the efficiency of green technology innovation, while the dependence of foreign capital on it was not obvious.

Zhang Feng,Ren Shijia,Yin Xiuqing. High-tech Industry Green Technology Innovation Efficiency and its Scale Quality Threshold Effect[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 59-68., doi: 10.6049/kjjbydc.2019080079.

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Research on Nonlinear Growth Genome Configuration and Equivalent Path of Venture Enterprises in New Economy

Wang Liping,Jin Binbin

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 69-78. https://doi.org/10.6049/kjjbydc.2019060019

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The rapid development of the new economy makes the entrepreneurs present different growth patterns and development paths from the traditional ones.From the three perspectives of endogenous,exogenous and networked growth,this paper uses the method of qualitative comparative analysis of fuzzy sets (fsQCA) from the perspective of configuration to explore the influence path of the combination of policy environment,regional industrial ecology,entrepreneurship team,value connection ability and network competence on the non-linear growth of new economic entrepreneurs.The research finds three paths,i.e.cross-border synergy of internal and external integration,singularity explosion of value connection and ecological empowerment of network aggregation.The results show that entrepreneurial team and value connection ability have positive effects on the high growth of entrepreneurial enterprises,and policy environment,regional industrial ecology and network competence play a vital role in the process of high growth of entrepreneurial enterprises.The conclusions enrich the growth theory of start-ups and provide reference and support of fast growth of start-ups under the new economic background.

Wang Liping,Jin Binbin. Research on Nonlinear Growth Genome Configuration and Equivalent Path of Venture Enterprises in New Economy[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 69-78., doi: 10.6049/kjjbydc.2019060019.

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Parent Company Holding,Financial Constraints and Enterprise Innovation

Liu Zhixiong

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 79-86. https://doi.org/10.6049/kjjbydc.2019090026

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Based on the data of Chinese listed companies from 2012 to 2017,this paper examines the effect of parent company holding on innovation investment.The results show that subsidiary companies are significantly less willing to invest in innovation.Further analysis shows that financial constraints weaken the relationship between parent company holding and enterprise innovation investment intention.After the transformation model estimation method and variable processing method,the conclusion is still very robust.This analysis provides empirical evidence for the limited liability theory of law and economics and the "prospect theory" and "threat rigidity model" of management,thus enriching the literature in these fields.At the same time,this paper has a certain reference significance for innovative management in group corporate governance in China.

Liu Zhixiong. Parent Company Holding,Financial Constraints and Enterprise Innovation[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 79-86., doi: 10.6049/kjjbydc.2019090026.

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Enterprise Innovation & Dynamic Adjustment of Leverage

Li Yichao,Xu Ting

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 87-94. https://doi.org/10.6049/kjjbydc.2019030110

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Based on the unbalanced panel data of listed companies in Shanghai & Shenzhen stock markets from 2008 to 2017, this paper comprehensively analyzes the dynamic relationship between enterprise innovation & leverage adjustment from the two dimensions of R&D efficiency & innovation output.The empirical results show that: in terms of the adjustment effect, high R&D efficiency & high innovation output are conducive to the downward adjustment of the leverage of enterprises.The heterogeneity of enterprise ownership will not change this leverage adjustment effect, but it shows obvious asymmetry, that is, the adjustment effect of state-owned enterprises is more prominent.In terms of acceleration effect, with the improvement of R&D efficiency & innovation output, the decline rate of leverage accelerates, state-owned enterprises are more sensitive to the acceleration effect of R&D efficiency, while non-state-owned enterprises are more sensitive to the acceleration effect of innovation output.

Li Yichao,Xu Ting. Enterprise Innovation & Dynamic Adjustment of Leverage[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 87-94., doi: 10.6049/kjjbydc.2019030110.

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R&D Cut under Real Earnings Management Motivation and Innovation Output-Research based on Innovation Output Quantity, Quality and Efficiency

He Yanan,Yuan Chunsheng,Feng Xiaoyu

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 95-104. https://doi.org/10.6049/kjjbydc.2018100637

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Taking Chinese A-share listed companies from 2007 to 2017 as the sample, this paper investigates the impact of firms' R&D cut under real earnings management motivation on their innovation output through identifying real earnings management motivation based on these there earnings benchmark: zero earnings, previous period's earnings, analysts' earnings forecasts.The findings show that, compared to other motivations, firms' R&D cut under real earnings management motivation will lead to lower innovation output, quality and efficiency in future three years.Furthermore, the results are still robust when the scope of earnings management identification is expanded, the whole sample is used for testing, and explained variables are replaced.

He Yanan,Yuan Chunsheng,Feng Xiaoyu. R&D Cut under Real Earnings Management Motivation and Innovation Output-Research based on Innovation Output Quantity, Quality and Efficiency[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 95-104., doi: 10.6049/kjjbydc.2018100637.

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University Scientific Research Governance: Conflicts and Reform

Fang Cheng,Fang Tongqing

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 105-112. https://doi.org/10.6049/kjjbydc.2019100680

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Building innovation-oriented country and “Double First-class” universities has been a national major strategic decision.In recent years, innovative initiative of researchers in university have been restricted and hard to be stimulated, which attracts the government’s attention and the public’s concern.In light of modern theory of conflict, this paper is going to study, in the process of university scientific research governance, the conflicts researchers in a subordinated position are facing; to elaborate the representation of conflicts, including intergroup conflicts, intragroup conflicts, subject conflicts and individual conflicts; to analyze the generation of conflicts, mainly including conflicts between hypothesis and expectation of government’s trust, conflicts between supply and demand of sci-tech system and conflicts between antagonism and cooperation of governance mode; to elucidate the theoretical logic of university scientific research governance, i.e.mutual trust is the premise of university scientific research governance, sci-tech system is the guarantee of university scientific research governance and collaborative work is the goal of university scientific research governance; and finally to propose a practical approach of reform that is to normalize the trust construction, systematize the sci-tech system, diversify system innovation, enhance the flexibility of governance mode, refine scientific research services and intelligentize governance measures.

Fang Cheng,Fang Tongqing. University Scientific Research Governance: Conflicts and Reform[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 105-112., doi: 10.6049/kjjbydc.2019100680.

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Research on the Excessive Rewards for Scientific Research in Public Universities

Yang Zhongtai

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 113-119. https://doi.org/10.6049/kjjbydc.2019060454

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It is the result of the measurement shows that based on the content of the policy text of "scientific research award method" of 70 public sample universities and the 651 frequency of 7 categories and 16 awards in total: Research achievements, especially academic papers, are the focus of the award object; the number of reward objects changes in the opposite direction with the types and levels of sample universities; there are serious duplicate awards for scientific research projects of all levels in universities of different types, especially in teaching universities, for ESI papers with high citation frequency; The amount of reward for scientific research projects also changes in the opposite direction with the types and levels of universities.Some teaching universities often have the phenomenon that the amount of reward for scientific research projects at all levels is greater than or equal to the funding of scientific research projects.To reward and over reward for scientific research in public universities is against the theory of scientific research labor and its input-output knowledge development process.It is must be ensure the basic recognition level and enhance reputation award; and improve and standardize the improvement layer and special reward layer.

Yang Zhongtai. Research on the Excessive Rewards for Scientific Research in Public Universities[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 113-119., doi: 10.6049/kjjbydc.2019060454.

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Analysis on Evolution Logic and Characteristics of Science and Technology Evaluation in China

Du Baogui,Wang Xin

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 120-129. https://doi.org/10.6049/kjjbydc.Q201908423

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Based on 2 698 literature related to Science and Technology Evaluation, the research utilizes co-word cluster analysis and social network analysis aiming at establishing genealogy charts and co-word networks of high-frequency keywords in different research stages, exploring changes and tendency of research topics. Overall, similarities and differences lie in research topics; Big transition of evaluation principles and guidelines occurs; The evaluation subject remains single; The range of evaluation objects is expanding, and classified evaluation has become a new trend; Evaluation methods are diversifying; The correlation degree and mutual permeability are enhanced.On this basis, the research figures out that the existing literature still has some limitations and gaps in the aspects of science and technology evaluation subject, object, index system establishment and evaluation method.

Du Baogui,Wang Xin. Analysis on Evolution Logic and Characteristics of Science and Technology Evaluation in China[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 120-129., doi: 10.6049/kjjbydc.Q201908423.

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An Evaluation of The Synergy of the Elements of Regional Innovation Ecosystem's Knowledge Ability

Hao Yingjie,Pan Jieyi,Long Yunguang

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 130-137. https://doi.org/10.6049/kjjbydc.Q201908153

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Knowledge capability is one of the most important dynamic capabilities of regional innovation ecosystem.According to the definition of regional knowledge capability, and regional innovation ecosystem theory, this paper constructs an index system of knowledge capability cooperativity of regional innovation ecosystem.Uses Shenzhen′s history statistical data, evaluates the synergy degree between knowledge innovation environment and knowledge base development of industry and academic.The main results show that the development of industrial knowledge foundation and academic knowledge foundation in Shenzhen is unbalanced, and the synergy degree of knowledge innovation environment and industrial knowledge base development in Shenzhen is higher than that of academic knowledge base.Therefore, the construction of Shenzhen′s innovation ecosystem should pay attention to the accumulation of academic and research institutions′ knowledge base, and strengthen the construction of regional knowledge innovation environment.

Hao Yingjie,Pan Jieyi,Long Yunguang. An Evaluation of The Synergy of the Elements of Regional Innovation Ecosystem's Knowledge Ability[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 130-137., doi: 10.6049/kjjbydc.Q201908153.

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How the Career Adaptability Influencing the R&D Employees' Turnover Intention

Li Yun,Li Xiyuan,Li Tai

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 138-144. https://doi.org/10.6049/kjjbydc.Q201908887

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If the Employees' career adaptability will enhance their turnover intention,or will weaken it? Based on the theory of career construction this paper analyzes the mechanism of career adaptability influencing the R&D employees' turnover intention in the special organizational circumstance in China.The results show that the R&D employees who have the stronger career adaptabilities tend to have the lower turnover intention,and the career growth opportunities play a mediated role between the career adaptability and the turnover intention.The employees who are more traditional will have lower turnover intention when they can get more and better career growth opportunities.The traditionality plays a moderated role to the mediated mechanism that the career growth opportunities have gotten between the career adaptability and the R&D employees' turnover intention.The career growth opportunity and the traditionaliy not only have answered that the R&D employees who have stronger career adaptabilities will have lower turnover intention,but also give some advices to the managers to leave the excellent R&D employees.

Li Yun,Li Xiyuan,Li Tai. How the Career Adaptability Influencing the R&D Employees' Turnover Intention[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 138-144., doi: 10.6049/kjjbydc.Q201908887.

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Employee Well-being, Job Stress and Innovation Behavior:Moderating Role of Perceived Organizational Support

Liu Lin,Mei Qiang,Wu Jinnan

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 145-151. https://doi.org/10.6049/kjjbydc.2019050293

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Based on the Theory of Resource Conversation, the broaden-and-build theory of positive emotionsand the Social Exchange Theory, this study built on a model for understanding how employee well-being influences innovation behavior with job stress as the mediator and perceived organizational support as the moderator.With 249 survey data collected from employees in Chinese IT firms, both hierarchical regression and bootstrapping analysis were conducted to empirically test research model.The results suggest thatemployee's well-being has significant positive impact on innovation behavior;employee's well-being has significant negative impact on job stress, which in turn significantly influences innovation behavior.Also, job stress partially mediated the relation between well-being and innovation behavior;(3) perceived organizational support positively moderates the process of job stress influencing innovation behavior, suggesting anefficient buffer of perceived organizational support.

Liu Lin,Mei Qiang,Wu Jinnan. Employee Well-being, Job Stress and Innovation Behavior:Moderating Role of Perceived Organizational Support[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 145-151., doi: 10.6049/kjjbydc.2019050293.

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Understanding the Core Mechanism of Platform Strategy:the Concept Evolution,Measurement Methods and Research Frontiers of Network Effects

Wang Jiexiang,Wang Yamin,He Jinjiang

SCIENCE & TECHNOLOGY PROGRESS AND POLICY. 2020, 37(7): 152-160. https://doi.org/10.6049/kjjbydc.201908961QZ

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Although a large number of studies have been based on the platform,they have not incorporated the core features of the "network effect" platform into the analysis and modeling,making this kind of research lack of theoretical depth.This paper combined the methods of bibliometric and content analysis to sort out the related research on network effects.It is found that the network effect research has experienced three theoretical evolutions,that is,the evolution of the same-side network effect to the cross-edge network effect,and what is the network effect to the network.What effect does the effect evolve,and the positive effect of the network evolves toward the negative effects of the network.The three major evolutions can also be seen in the measurement of network effects and industry contexts.Combined with keyword mutation analysis,the latest research on network effects has begun to shift from focusing on the “consequences” of network effects to “proactive causes”.Combined with the latest research trends of strategic management,this paper proposes that the future network effect precaution research can be carried out from four levels: individual behavior,relationship embedding,population ecology and institutional environment.Especially with the platform model extending from the Consumer Internet to the Industrial Internet,the role and stimulation of the network effect is a very important research topic.

Wang Jiexiang,Wang Yamin,He Jinjiang. Understanding the Core Mechanism of Platform Strategy:the Concept Evolution,Measurement Methods and Research Frontiers of Network Effects[J]. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2020, 37(7): 152-160., doi: 10.6049/kjjbydc.201908961QZ.

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10 April 2020, Volume 37 Issue 7

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10 April 2020, Volume 37 Issue 7