The discussion on biological phenomena of synthetic biology has changed from cognition to synthesis, and the research object has shifted from natural life to synthetic life, which has caused a lot of ethical issues and debates. At present, the academic circles discuss this issue in multiple dimensions, but the characteristics and relations of different dimensions, as well as the internal correlation between the debates of various dimensions and the development stage of synthetic biology are relatively weak. This paper reviews the ethical controversies in synthetic biology and summarizes the five main dimensions and characteristics of the ethical debates, specific include: the legitimacy of making living organisms, the challenge of technological development to religious culture, the ethical issues of biological safety, the fairness of profit and risk distribution, the conflict between freedom of action and ethical supervision. At the same time, this paper starting from the development stage of synthetic biology, analyzes the internal logic of the gradual development and mutual influence of different dimensions of ethical debates. The discussion in this paper is helpful to clarify the chaotic state of the ethical research of synthetic biology, deepen the understanding of the core proposition and its basis of different ethical standpoint in the ethical debate of synthetic biology, and then clarify the key issues to be solved in the ethical governance of synthetic biology.
The existing "Jamieson’s Principles"、"Oxford Principles" and "Tollgate Principles" in geoengineering define its responsibility subject and action framework clearly. Nevertheless, they make slightly insufficient ethical requirement for the experimental process and actual deployment and ignore the realistic problems on how to deal with negative effects made by geoengineering. Responsible stagnation, a new concept proposed in the questioning of responsible innovation research, is a protection mechanism. Firstly, it criticizes meaningless experimental projects that deviates from human well-being at macro level, advocating that innovations stem from responsibility; secondly, it requires that in extreme cases, social and extremely dangerous Innovation activities be stagnated so as to ensure human safety and buy time to nurture effective responses. Finally, it requires, at micro level, the responsibility-oriented experimental design to be reconstructed, experimental deployment with moral constraints to be deconstructed and a solid law for resolving crises with stagnation as the dual guidance to be constructed. The principle of responsible stagnation makes up for the lack of ethical guidance and remedial measures for the existing principles of geoengineering in the process and result stages.
The keys of pre-registration for solving the reproducibility crisis are to admit bias, register bias and reproduce bias, as well as the construction of a whole data-chain from idea to publication. The system of pre-registration could control the following four bias in the research process: Firstly, registration of pilot data provide the data basis for preservation and disclosure of confirmation bias. Pilot data should be published, so as to improving data reproducibility of experiment design. Secondly, incremental discoveries should be unloaded to control hindsight bias, as well as provide database for reproduce hindsight findings. Thirdly, second peer-review should also evaluate the implementation degree of registered data-analysis methods, in order to control selective reporting bias such as floor effects, ceiling effects, p-value effect etc. Fourthly, pre-registration must publish null results to control publication bias.
Nowadays, artificial intelligence (AI), as a main force leading the new round of disruptive industrial change, begin to spread and accelerate enabling in various fields. Meanwhile, the artificial intelligence enables the “double transition” of technology innovation and application innovation, which puts forward emerging challenges to sectoral innovation ecosystem (SIES) from multi-dimensions, such as the production factors, the function boundary, the interaction relationship, etc. The transitions of SIES empowered by AI leads to following thinking in this paper: what original changes will AI enable the main composition and biological community of SIES? What breakthrough changes will AI enabling make in the main ecological position and interactive relationship in SIES? What disruptive changes will take place in industrial pattern due to the transitions of SIES empowered by AI? Learning lessons from theories of nature ecosystem and SIES, this paper constructs the theoretical framework of dual-transition (including core driving layer -industrial pattern change layer) empowered by AI, and the operation logic and industrial revolution within SIES are analyzed by the case study of autonomous driving. It mainly includes two steps in this part. First, based on the theoretical framework of SIES transition, this paper reveals the dynamic process of “core drive leading to industrial change”, and explains the new interactions among innovators in the SIES. To explore the core driving layer, the article also draws the cross-sectional view of the evolution from “traditional quadruplex helix” to “emerging quadruplex helix”, which also explains the generation of multi-homing actor and secondary communities in the SIES. Second, taking autonomous driving as an example, this paper gives the keywords’ co-occurrence network of autonomous driving SIES, and makes practical analysis on four aspects of SIES transition empowered by AI. The research findings are as follows: first, the emergence of multi-homing actor and secondary communities give rise to the new ecological interaction of SIES, and it becomes the core driver pushing SIES from traditional quadruplex helix to emerging quadruplex helix. Second, the interaction of core driving and industrial change are increasingly enhanced, and multi-homing actor and secondary communities continuously trigger industrial practice changes. These make characteristics of industrial patterns tend to reconstruct of value distribution, upgrade of intelligent manufacturing, adaptation of business model, and revolution of organizational decision-making. All in all, an emerging SIES integrating “core driving layer - industrial pattern change layer” empowered by AI is becoming clearer and clearer. This paper contributes to existing research in the following two aspects: first, it puts forward and demonstrates new concepts of multi-homing actor and secondary communities. And it explains the emerging quadruplex helix innovation by exploring secondary communities including technological innovation, product manufacturing, market application and policy regulation. By interpreting the existence of multi-homing actor and secondary communities, this paper break through the theoretical dilemma about the fuzzy function boundary in SIES. Second, by describing the industrial patterns and emerging characteristics empowered by AI, this paper verifies the practical transition (such as reconstruct of value distribution, upgrade of intelligent manufacturing, adaptation of business model, and revolution of organizational decision-making) of autonomous driving SIES, which strongly proves that AI enabling is triggering ubiquitous changes in industrial patterns.
The information asymmetry behind the "algorithm black box" will bring social risks. In the development of artificial intelligence technology, the principle of transparency is the prerequisite and basis for algorithm supervision and the establishment of trust relationships. The development of intelligent industries and social trust benefits also call for the principle of transparency. However, due to obstacles such as conflicts of interest, technical characteristics, and institutional costs, the thorough, full openness and transparency in the traditional field should not be adopted to supervise the artificial intelligence technology, but instead requiring limited and reasonable transparency standards. The effective implementation of this standard relies on the synergy of the governance of conduct and the protection of private rights, the entire process control of artificial intelligence such as pre-prevention, interim restraint, and post-relief, combined with the subject, object, degree, and conditions in contexts, in order to realize the balance and coordination between intelligent technological innovation, overall economic benefits and social public interests.
Cloud computing is an important part of China’s "new infrastructure" strategy. In order to enhance the city's digital competitiveness in cloud computing, many local governments construct technology parks and innovation bases to promote the agglomeration of cloud-computing firms in the local city. The logic behind these actions is the belief that agglomeration brings innovation. Recent years have witnessed the spatial clustering of cloud-computing firms in many cities such as Shanghai, Beijing, and Shenzhen. However, whether the traditional wisdom, which is borrowed from the practical experience from the manufacturing and service industries, fits the innovation pattern in the cloud-computing industry, is still a question to be answered. The cloud computing industry is different from the traditional industry in the “localization” pattern. Instead of having to install hardware and software on site, the IT resources of cloud computing can be delivered through the Internet. From the technical logic, this new cross-space "pay-as-you-go" model largely dissolves the limitations of location and geographical distance. The seemingly contradictory relationship between the government's regional policies to enhance industrial agglomeration and the virtualized and networked technological attributes of cloud computing is the starting point for this exploratory study. At the spatial scale of intra-city micro-locations, a few understudied questions attract our interest. First, does the cloud computing industry exhibit spatial agglomeration characteristics? Or, does it follow the technological logic and exhibit spatially decentralized and suburbanized distribution characteristics? Second, for cloud computing firms, what impact do different degrees of agglomeration and agglomeration patterns have on firms’ technology innovation? Third, does the innovation effect of agglomeration vary with different technological layers along the industry chain (basic layer, platform layer, and software layer)? To answer these questions, this paper collects data on 1637 cloud computing firms in Shanghai from 2010-2016. Combining text analysis, spatial analysis, and econometric modeling, this study aims to depict the spatial characteristics of the intra-city cloud computing industry and to analyze the effect of different agglomeration patterns on enterprise innovation. The quantitative analysis offers novel findings. (1) Shanghai's cloud computing industry shows a spatial pattern of central clustering and multipoint linkage. As the industrial chain extends toward the back end, the spatial distribution of enterprises clusters more and more toward the central city. (2) The cloud computing industry is still geographically relevant. Specifically, the geospatial agglomeration still significantly affects technological innovation. (3) More interesting, specialized agglomeration and diversified agglomeration within the industry chain have different effects on different types of cloud computing enterprises. Specifically, as the technology chain extends to the market side, the impact of specialized agglomeration on enterprise innovation turns from negative to positive and increases sequentially; however, the innovation promotion effect brought by diversified agglomeration turns from positive to negative and gradually decreases. This study responds to the academic debate on whether geography is dead since the rise of the Internet. The findings not only show that the cloud computing industry with the attributes of virtualized technology still shows the spatial distribution characteristics of geographic agglomeration but also further verify the impact of spatial agglomeration on technology innovation. At the same time, this study is a strong complement to the existing agglomeration theory. The research findings also provide realistic reference implications for cloud computing industrial policies.
Abstract:
The fourth industrial revolution is coming at an unprecedented rate, followed by the digital industry's disruptive innovations and new business formats rewriting the global manufacturing competition pattern. In such a case, technology standards, tightly bound with intellectual properties, are re-designing the global competition rules in the digital world. On the other hand, the lack of interconnection standard agreement caused the "Isolated Data Island," strangling the further development of the digital industry. Therefore, developing supervising principles for digital technology standards and strengthening the protection and use of intellectual property rights is essential to accelerating digital industrial innovation. However, most existing research focuses on theories and practices about digital innovation or digital industry, leaving a research gap in the systematic definition of digital industrial innovation and the mechanism of technology standard and intellectual property's co-promotion on digital industrial innovation. Based on the systematic review of the collected findings, this study expects to explore a theoretical framework to figure out how technical standards and intellectual property co-promote innovation in the digital industry and refine potential future research.
To this end, the research is organized as follows. First, we use VOS Viewer to compile 268 articles published in international critical journals between 2000 and 2020. Based on the systematic review, we further put forward the extension of the innovative connotation of the digital industry and a theoretical framework of follow-up research. As many colleagues and peers proposed, the digital industrial innovation introduces the data as a factor of production and a production condition into the economic system to obtain a new type of production function through the "new combination." From such a perspective, creative destruction constructs the endogenous foundation of digital industrialization and industrial digitalization and consequently produces a new business format. On this basis, we summarize a framework to explain how technical standards and intellectual property co-promote digital industrial innovation as the "interaction relationship (co-propulsion)-intrinsic mechanism (eight-force drive) -action path (two-way interaction)" model. The model helps to analyze the dynamics and laws of its continuous development and evolution from technological and organizational change.
Next, based on the two dimensions, the type of digital industrial innovation output and the synergy ability technical standard and intellectual property, the paper constructs a four-quadrant analysis frame of the efficient combination of digital industry's melting and re-engineering new business format. The frame draws four differentiated re-engineering modes: intellectual property-driven personalized customization, technology standard-driven intelligent production, standard-oriented network collaboration, and technology-based collaborative service extension. Based on the technology standard strategy, intellectual property strategy, and digital industrial innovation collaborative strategy, the construction strategy of the digital industrial innovation ecosystem is eventually coming out. Finally, the paper puts forward the future research alternatives and suggests focusing on the cooperative interaction between technical standards and intellectual property rights in the context of digital industrial innovation, the new content of promoting the innovation process mechanism of the digital industry, and the new field of co-promoting, aiming to form a research force and promote the further development of digital industrial innovation research.
To sum up, this study develops the connotation and extension of digital industrial innovation. Furthermore, it puts forward the mechanism through which technology standard and intellectual property co-promote digital industrial innovation and re-engineer new business format, making up for the gap in the theoretical research. Therefore, this paper has significant theoretical value and practical guidance to promote the rising along the digital industry value chain to the high-end and enhance international competitiveness.
The combination weighting method is used to determine the weight of order parameter index, and the traditional composite system synergy degree model is improved. A comprehensive measurement model of intellectual property（IP） management capability synergy degree with speed characteristics of patent intensive industries is constructed. Based on the sample data of 15 patent-intensive industries from 2011 to 2016, this paper makes an empirical study on the collaboration and evolution of intellectual property management capability of China's patent-intensive industries from the static and dynamic perspective. The results show that the development level of synergistic degree of IP management ability of China's patent-intensive industries is low, and the synergistic degree fluctuates in the range of [-0.08, 0.1]. The collaborative development of IP management ability of different patent-intensive industries is relatively unbalanced. The collaborative computer manufacturing industry is relatively low and ranks low. The medical equipment manufacturing industry, pharmaceutical manufacturing industry, electrical equipment manufacturing industry, chemical raw materials and chemical products manufacturing industry is relatively stable, ranking top. In addition, the coordinated development of the patent intensive IP management level showed obvious trend of fluctuations, in addition to the manufacturing of communication equipment, radar and auxiliary equipment and other electronic equipment, other patent-intensive industries show an upward trend, indicating that most industries can develop in a balanced and orderly way. The research conclusions are expected to provide theoretical basis and policy suggestions for the improvement of the coordination degree of IP management ability in patent-intensive industries.
With the emergence and accelerated evolution of a new round of scientific and technological revolution and industrial change, the disciplinary composition system of contemporary science and technology has become more and more complex, and scientific research activities across traditional boundaries have become the growth point of the new contemporary scientific and technological revolution. At the same time, the global economic landscape has entered a period of deep adjustment, science and technology has become the main force driving economic and social development. The superposition of the demands of science and technology development and the urgent requirements of economic development for science and technology support, coupled with the support of digital infrastructure and conditions, science and technology innovation activities continue to break through the boundaries of geography, organization and technology, thus promoting the rise of new research organizations with integrated functions for industry, of which new R&D institutions are typical representatives. In response to the innovation and research organization paradigm shift, innovative R&D institute construct the logic of knowledge transfer with new organizational patterns and institutional forms.
Based on four typical cases, namely, Research Institute of Tsinghua University in Shenzhen established mainly by universities, Shenzhen Institutes of Advanced Technology of Chinese Academy of Sciences established led by research institutes, Shenzhen Institute of Beidou Applied Technology set up by enterprises, and Peng Cheng Laboratory led by the government, explores the inner mechanism of how innovative R&D institutions can promote the efficiency of knowledge transfer through new functional design. Due to the reticence and embeddedness of knowledge, knowledge transfer is a complex process, as it is divided into knowledge identification, knowledge processing, knowledge dissemination and knowledge application. A research framework with the knowledge transfer process as the main line is established, focusing on the analysis of the internal organization mechanism of innovative R&D institutions based on knowledge in the transfer process and the interaction mechanism with each subject of knowledge transfer in the four stages of knowledge transfer. The results show that innovative R&D institute promote the efficiency of knowledge transfer significantly by playing the following ways. (1) The innovative R&D institutions construct the market-oriented knowledge value identification function and enhance the motivation and capability of knowledge identification. (2) The innovative R&D institutions develop the knowledge processing function based on application scenarios and form the knowledge processing capability supported by professional teams, equipment and platforms. (3) The innovative R&D institutions construct the function of promoting knowledge manifestation, reduce the embeddedness and reticence of knowledge and enhance the efficiency of knowledge dissemination. (4) The innovative R&D institutions improve the function of serving knowledge recipients to apply knowledge and reduce the risk of using new knowledge by knowledge recipients.
Based on the findings of the study, the following policy recommendations are put forward. First, the development orientation of innovative R&D institutions should be clarified, and they should be guided to carry out industry-oriented knowledge transfer activities. Second, encourage and support innovative R&D institutions to develop around the knowledge transfer function and carry out innovations in organization mode, management mechanism, incentive mechanism and operation mode. Third, according to the difference between innovative R&D institutions and traditional research organizations, precise policies should be formulated according to the characteristics of innovative R&D institutions.
New product development (NPD) is a key part of enterprise management and an essential way for enterprises to obtain sustainable competitive advantages. In the context of economic transformation, Chinese enterprises always survive in an environment of high uncertainty and low munificence. Under this circumstance, enterprises gradually realize that it is really necessary to introduce decision-making logic to promote new product advantages (NPA). Effectuation decision-making logic is often adopted by enterprises under conditions of high uncertainty, which emphasizes that experimenting and interacting repeatedly, taking a set of available means and investing resources within the scope of risks that enterprises could take, grasping or creating opportunities by obtaining pre-commitments with stakeholders in advance and making full use of external contingency factors. However, there are some deficiencies in the research of effectuation in NPD. First, previous studies focused on the discussion in an entrepreneurial context and paid less attention to effectuation decision-making logic in the NPD context, such as the discussion on the inner mechanisms between effectuation and NPA. Second, few studies shed light on the mediating mechanism between effectuation and two types of NPA.
Based on the summary of relevant theories and existing studies, according to effectuation theory, this paper first analyzes the impact of effectuation on different dimensions of NPA. Then, based on the knowledge-based view, on the one hand, it explores the differentiated effects of two types of external knowledge search on NPA. On the other hand, it discusses the different mediating mechanisms of external knowledge search between effectuation and NPA. In this study, 256 valid samples were obtained by face-to-face interview, e-mail, and postal questionnaire survey methods. All hypotheses were verified by empirical analysis and were supported. The results show that effectuation positively affecting the NPD speed and New product creativity (NPC), and effectuation positively affecting reactive search and prospective search at the same time. Moreover, the positive impact of reactive search on NPD speed is stronger than prospective search, but the positive impact of reactive search on NPC is weaker than prospective search. More specifically, reactive search plays a mediating role between effectuation and NPD speed, and prospective search plays a mediating role between effectuation and NPC.
First, this study expands the application contexts of effectuation theory. Our study not only enriches the research on the antecedent variables of NPA, but also provides a new perspective for the following studies on NPD activities. Second, based on the knowledge-based view, this study answers the question of "what kind of intermediary mechanism does the effect logic use to obtain the NPA" by introducing the mediating role of external knowledge search. As a learning strategy, knowledge search promotes the acquisition of NPA by interacting with the external environment, and expands firms’ knowledge resource base with effectuation logic. Thirdly, based on the existing research on the division of knowledge search, this paper explores the differential role of reactive search and prospective search strategies, and improves the related research of knowledge search in the context of NPD.
In the entrepreneurial ecosystem, corporate venture capital (CVC) is an effective mechanism to promote the open innovation of large enterprises and the rapid growth of start-up enterprises. CVC practice activities have been carried out in China for 20 years, which has promoted the common development of large enterprises and start-up enterprises, and formed a symbiotic relationship between them through the optimization of symbiotic media and symbiotic interface, mutual benefit and symbiosis, can be realized. From the perspective of innovation ecosystem, the stable symbiotic relationship between large enterprise population and entrepreneurial enterprise population can be formed through evolutionary game, which is conducive to improving the adaptability of both sides and broadening the niche, and then co-exist to create value. The niche of CVC ecological community was described and the innovation of CVC ecological community was analyzed through the introduction of Lotka-Volterra model. This paper analysis the stability of evolution game through Replicator Dynamic Equation, and then discusses ten parameters of niche state. The evolution trend of innovation niche of large enterprises and start-up enterprises is obtained through simulation examples. Finally, the symbiosis cultivation mechanism of the ecological community of venture capital is proposed from the perspective of symbiosis, learning, innovation and incentive mechanism. It provides theoretical support for strategy optimization and selection of enterprise innovation niche in China's CVC ecological community. The cultivation and evolution of CVC ecological community is based on the formation of symbiotic relationship. The professional advantages and abilities of large enterprises and start-ups are the basis of their participation in symbiosis. The complementarity among multiple subjects makes them interdependent. Based on the common goal and mutual trust among subjects, they form a close relationship and gradually evolve into a stable symbiotic relationship. CVC ecological community's pursuit of symbiotic interests is its instinctive motivation. Due to the complementarity of resources or knowledge, the integration of culture and the persistence of trust among symbiotic subjects, it can bring a variety of shared interests such as technological innovation, resource acquisition, cost reduction, risk control and scale benefits in the process of symbiosis. The niche evolution of CVC ecological community is affected by a variety of mechanisms. Competition and symbiosis are driven by interests and affected by ecological balance. Interest driven mechanism is the internal growth mechanism of CVC ecological community in a certain innovation and entrepreneurship ecological environment. The power source is the pursuit of maximizing individual interests by large enterprises and entrepreneurial enterprises. Large enterprise population and entrepreneurial enterprise population integrate relevant resources through horizontal symbiosis, vertical symbiosis or dynamic alliance, eliminate or reduce resource bottlenecks, and promote the smooth development of large enterprises and entrepreneurial enterprises. Therefore, as a core part of the innovation and entrepreneurship ecosystem, CVC ecological community shows a nonlinear and exponential growth trend. Only through effective symbiotic cultivation, symbiotic energy will be continuously generated and guide the circular development of new symbiotic relations in evolution. As an important mechanism in the entrepreneurial ecosystem, CVC ecological community symbiosis cultivation mechanism maintains the stability of symbiotic relationship through value co creation and distribution through adaptation, adjustment and aggregation among system populations, so as to promote the balance and healthy development of the ecosystem and the continuous improvement of the value of the whole innovation ecosystem.
In the management of modern enterprises,innovation is the source of keeping vitality.The performance of technological innovation determines the level of enterprises innovation achievements, is one of the important indicators to measure the innovation ability of enterprises. In recent years, it has become a hot topic of management research. Scholars are committed to finding out the internal and external factors of enterprises and exploring their influence mechanism, in order to improve the technological innovation ability of enterprises, and enhance independent innovation,realize the healthy and rapid development of enterprises. Among the many factors that influence the performance of technological innovation, the investment in R&D is the first fundamental one,as well as the important guarantee. In the research of enterprise management behavior, the research on Cost Stickiness is an important way to reveal the "management black box" of enterprises. The existing research on Cost Stickiness can be divided into "Favorable Theory" and "Unfavorable Theory", both of which reflect the importance of Cost Stickiness in enterprises. On that basis, this study focuses on the R&D investment and want to explore the impact of the existence of R&D Cost Stickiness on the firm's technological innovation performance.Therefore on the basis of a large number of literature research redefined the Stickiness of R&D Cost, namely the relationship between enterprise innovation input and business volume change is not strictly matched, and has established the relationship between the Stickiness of R&D Cost and performance of technological innovation.In this process,also further analyzed the enterprise scale and the intermediary effect of financing constraints.
This paper specifically studies the Stickiness of R&D Cost,choose the data of listed industrial enterprises in China from 2015 to 2019 as samples, uses the model of WEISS to measure the Stickiness of R&D Cost in enterprises, and set up the relationship model of R&D Cost Stickiness and technology innovation performance, conducts multiple regression analysis,multiple regression analysis is carried out to empirically test the influence of R&D Cost Stickiness on technological innovation performance, and analyze the performance of this influence under different property rights.The results are as follows:As the general Cost Stickiness, the Stickiness of R&D Cost is common in listed firms, is a common phenomenon existing in the listed companies in China.Different enterprises have different R&D Cost Stickiness, and it has a significant positive effect on the performance of technological innovation of enterprises, which is helpful to improve the performance of technological innovation. In the further empirical analysis found that corporate R&D Cost Stickiness of positive influence on the technological innovation performance of mechanism was more marked in non-state-owned enterprises.At the same time, under the influence of enterprise scale effect and financing constraint conditions, the promote significant effect of R&D Cost Stickiness to the technological innovation performance exists but still relatively weak.Further analysis shows that although there is a positive correlation between firm size and technological innovation performance, but the promotion effect of R&D Cost Stickiness on technological innovation performance weakens under the effect of scale effect. Secondly, financing constraints have a restrictive effect on R&D Cost Stickiness to a certain extent, then affect the promoting effect of R&D Cost Stickiness on technological innovation performance. Finally, putting forward some proposals according to the results of the study, the existence of R&D Cost Stickiness is positive, helps to improve the performance of enterprise technology innovation.So, in order to improve enterprise's technology innovation performance and capacity for independent innovation,enterprise should encourage attach importance to research and development, reasonable increase R&D investment,at the same time, pay attention to strength the relevant aspects of improving innovation performance.
External collaboration is important for incumbent firms to enlarge necessary new knowledge elements and recombination paradigm for innovation, while internal knowledge networks can affect its effectiveness. We distinguish two types of external collaborations, academic collaboration, and industry collaboration, and analyze how their effectiveness on innovation was affected by the structure of internal knowledge networks. Employing a dataset of 323 listed companies in the communication industry and pharmaceutical industry in China, from 2012 to 2017, we found that firms with external collaborations, particularly firms with more academic collaborations—have a higher innovation performance than their non-connected counterparts. Firm’s internal knowledge recombination potential, measured by the weighted clustering coefficient and average path length of the firm’s internal knowledge network, will weaken the impact of academic collaboration, but contribute to the impact of industry collaboration. A firm’s internal knowledge coordination cost, measured by average ties per inventor in the firm, can weaken the positive relationship between industry collaboration and firm innovation.
The development level of high-tech industry is related to the comprehensive competitiveness of a country or region. Scientific and effective evaluation of the innovation process efficiency of regional high-tech industry is of great significance to enhance the innovation ability of high-tech industry. This paper uses the three-stage chain relational network DEA model to measure the overall efficiency and three sub stage efficiency of high-tech industry innovation in China's provincial regions, and analyzes the correlation effectiveness between the sub stages of innovation system and the differences of regional innovation process efficiency. The overall efficiency and three-stage efficiency in China's high-tech industry have been improved to varying degrees, but on the whole, the value of innovation efficiency is not high, especially in the overall innovation efficiency and the efficiency of achievement transformation. Through the classification analysis of innovation efficiency, it is found that only a few regions have relatively high efficiency in the three stages of knowledge production, technology research and development and achievement transformation, which indicates that the innovation efficiency of most regions in China is not high. It is necessary to take corresponding measures to improve according to the low efficiency link in the innovation process.
Based on social network theory, resource-based view and the growth curve model, the effects of intra-community structure dynamics (intra-community stability, intra-community expansion) and inter-community structure dynamics (inter-community expansion) on enterprises’ innovation performance in the innovation network under different technology life cycle stages are investigated. Using SDC database, USPTO, JPO, EPO and the national patent database of the sample enterprises, the empirical research is carried out with the alliance enterprises in the field of communication equipment as samples. The results show that in the technological emerging period, inter-community expansion have a negative impact on innovation performance; in the technological growth period, inter-community expansion and intra-community stability has a positive impact on innovation performance; in the technological maturity stage, intra-community stability has a positive impact on innovation performance, while intra-community expansion and inter-community expansion have a negative impact on innovation performance. On this basis, the paper puts forward policy suggestions to improve enterprises’ innovation performance by adjusting the innovation cooperation network in different life cycle stages.
Science and technology aid to Xinjiang is a major strategic measure for the state to promote independent innovation and self-development in Xinjiang border minority areas, and to solve the imbalance and insufficient contradiction of regional development. Based on the panel data of 11 provinces in the western development from 2003 to 2017, this paper empirically tests the impact of science and technology aid strategy on Xinjiang's innovation ability by using the double difference method. The results show that: The strategy of aiding Xinjiang with science and technology has a significant negative impact on Xinjiang's innovation ability, which indicates that the strategy of aiding Xinjiang with science and technology has failed to effectively improve Xinjiang's innovation ability; The dynamic effect analysis also shows that the strategy of science and technology aid to Xinjiang not only fails to improve Xinjiang's innovation ability, but also leads to the "policy trap" of Xinjiang's regional innovation development; The results of further impact mechanism test show that technology effect, allocation effect and structure effect play an intermediary role in the impact of science and technology aid strategy on Xinjiang's innovation ability, but the three effects fail to play an effective role, resulting in the "low efficiency trap" of science and technology aid innovation resources accumulation, the insufficient role of market allocation of innovation resources in Xinjiang, and the low efficiency trap of science and technology aid innovation resources accumulation The important reasons for Xinjiang's regional innovation and development to fall into the "policy trap" are the dependence of industrial enterprises on policies and the crowding out of competitive enterprises.
39 new research and development institutions in Guangdong province were selected as the research samples, this paper uses the method of fuzzy set qualitative comparison (fsQCA) to explore the influencing factors of high innovation performance of new R&D institutions and the promotion path. The results show that: (1) it is difficult for a single factor to promote the new R&D institutions to achieve high innovation performance, but the combination of different factors has a significant impact; (2) there are five problems There are three ways to drive high innovation performance: technology driven government support, technology driven environment support, organization supported ecological promotion, ecological support talent promotion and full dimension collaborative; (3) the driving mechanism of non-high innovation performance is divided into one path, and there is an asymmetric relationship with the driving path of high innovation performance. The research conclusions not only expand the theory of performance management of new R&D institutions, but also provide decision support for the government and new R&D institutions to optimize the path of performance improvement.
