Digital innovation ecosystem is characterized by digitalization of innovation elements, virtualization of actors and ecological relationship among actors, which bring challenges to its governance. Starting with the characteristics of digital innovation ecosystem and its governance dilemma, this paper constructs the theoretical framework of digital innovation ecosystem governance from three aspects: relationship mechanism, incentive mechanism and control mechanism. In addition, the governance mechanism of digital innovation ecosystem is realized through digital platform construction, digital technology application and digital resource coordination.
This study focuses on the intelligent manufacturing, which is the developing trend and hotspot of manufacturing industry, and discusses the potential advantages and problems that may come along with the hardware and technology upgrading of IOT (Internet of Things)-based intelligent manufacturing. We further explore the importance of constructing a three-network-integrated intelligent manufacturing ecosystem through introducing Internet of Service and relationship network (guanxi network). This study also illustrates how to integrate three networks to achieve effective coordination and reduce cost, and proposes several corresponding management emphases. Our findings suggest that traditional IOT-based intelligent manufacturing not only brings development opportunities, but also causes specific problems. Through introducing Internet of Service and relationship network (guanxi network), the construction of three-network-integrated intelligent manufacturing ecosystem can better deal with the potential management problems and challenges.
Based on the value creation and value co-creation logic of the innovation ecosystem, this paper points out that the operation of the digital innovation ecosystem needs the support of industrial data and public data, and the evolution of the digital innovation ecosystem needs the guidance of commercial value and public value. The development of "Aim High" and the governance of "Aim Steady" are both necessary.
The paper builds a two-stage dynamic DEA model from the perspective of the innovation value chain, and employs the model to analyze the R & D efficiency, export transformation efficiency, comprehensive efficiency and intertemporal dynamic change on the basis of 52 national high-tech parks panel data in China over the period of 2006-2017. The influencing factors are also analyzed by regression simultaneously. The results show that the average R & D , export transformation, and comprehensive efficiency of these areas show an upward trend in fluctuation as a whole, and the average value of the export transformation efficiency is the lowest among the three. In addition, the economic development and talent number of high-tech zones have a significant positive impact on the R & D innovation efficiency, the opening degree,debt financing, and the R & D innovation efficiency of these cities play a clear positive role for the export transformation efficiency, and geographic distance brings a noticeable negative effect on the export transformation efficiency. These research results provide a certain theoretical support for the implementation of China's innovation-driven development strategy, and related policies for promoting R & D innovation and export transformation in high-tech zones.
To explore the characteristics and differences of key general purpose technologies (GPTs) cooperation networks in different industries, cooperation networks are constructed based on the cooperation patent data of key GPTs of five industries in China. The social network analysis method is used to compare and analyze the characteristics of network structures evolution, the space characteristics of R&D entities, and the characteristics of industry-university-research cooperation of the key GPTs cooperation networks in five industries from 2000 to 2018. Furthermore, the development laws of key GPTs cooperation networks in different industries are summarized followed by some beneficial inspirations. The present research results show that the key GPTs cooperation networks of five industries have dynamic evolution characteristics, and there are commonalities and differences in network structure during evolution. In the key GPTs cooperation networks of five industries, the spatial distribution of R&D entities shows different degree of clustering. The influence of different regions in different industries area cooperation is difference. Moreover, the enterprise-enterprise cooperation is the main cooperation pattern in the key GPTs cooperation networks of five industries. The degree of industry-university-research cooperation in various industries can be improved. The conclusions are of significance for formulating differentiated policies and developing distinctive cooperation models for key GPTs in different industries.
Abstract: the purpose of this paper is to research the driving factors of technical cooperation and to explore its influence factors at the national level. Assume the influence of technological proximity on the existence of international technical cooperation, using proximity analysis method, considering the moderator variables of social proximity and geographic distance, with patent cooperation data between the belt and road countries, using social network analysis of quadratic assignment problem (QAP) method. Research has shown that technological proximity with the international technology cooperation between the belt and road countries is inverted u-shaped relationship, social proximity and geographic distance adjust the impact. Result means too high or too low technology combination of homogeneity was unfavorable to increase technical cooperation performance, at the same time national geographic distance slow effect of technical proximity to the international technology cooperation. This study provides reference for the planning of international technical cooperation.
Block grant and project funding are the two main modes for government research funding. Scientific analysis of the differences between the two funding modes is of great significance for the rational design of government research funding mechanisms. Multi-dimensional information contained in the output of these two funding modes from 2009-2018 in chemistry from Japan are taken as research objects Three-dimension analysis framework is built. In terms of methods, deep learning algorithms are introduced, and a training model for research object entity recognition in the field of chemistry is established, which realizes accurate recognition of research object entities and provides a factual basis for the analysis of funding differences. Data analysis results show that block grant and project funding have significant differences in multiple dimensions. The scientific research activities funded by block grant are more concerned in the research problem itself, while the scientific research activities funded by projects are more reflect the selection criteria from scientific community for projects. Policy recommendations of scientifically understand the difference between the two funding modes, rational layout, advancing strengths and avoiding weaknesses to establish efficient government research funding mechanism are proposed combing the data analysis results.
The virtual, integrated, and diversified trend is an essential feature of research teams in the new round of scientific and technological revolution. Exploring factors affecting the performance of research teams under the new development trend is of great significance to promote the researchers' performance and to improve the national scientific and technological innovation strength. On the basis of extensive literature review, this paper investigates the impact of six factors on the performance of research teams (quantity and quality of academic papers), namely team size, institutional diversity, country diversity, interdisciplinarity, the richness of funding sources, and team instability. The results indicate that the quantity of scientific team output is positively related to team size, institutional diversity, and richness of funding sources, and negatively related to country diversity, interdisciplinarity, and team instability; the output quality is positively related to the richness of funding sources, and negatively related to institutional diversity.
International development strategy is a key path for latecomers’ capability accumulation and upgrading. Taking Lenovo and Huawei as examples, this paper analyzes capability upgrading mechanism in firms’ international development process based on the method of case study. The results show that: (1) Exploitative learning strategy and explorative learning strategy are the main learning strategies in latecomers’ international process. Firms take exploitative learning strategy in the models of overseas merge & acquisition and overseas subsidiaries, and take explorative learning strategy in the model of R & D globalization. (2) The dual learning mechanism based on exploitative learning strategy and explorative learning strategy is the key capability upgrading mechanism in the internationalization of latecomers. (3) There are two stages for latecomers’ capability upgrading: factors accumulation and capability improvement.
In the uncertain environment of entrepreneurship, how to make decisions is a topic worth discussing. Starting from the psychological activities of entrepreneurs, this study explores the influence mechanism of entrepreneurs' heuristic decision logic and collects two groups of samples from China and the United States. Through the structural equation model empirical analysis of 171 samples from China and 116 samples from the United States, it is found that perspective taking and entrepreneurial passion are important antecedents of entrepreneurial decision-making logics, self-efficacy plays a mediating role in the relationship between perspective taking and decision making logics as well as in the relationship between entrepreneurial passion and decision making logics. Through the cross-country test, the research results indicate to have universal significance. This paper extends the research on the formation mechanism of entrepreneur's decision-making logics. The conclusion is helpful for entrepreneurs to scientifically make decisions.
This paper conducts an empirical study on the relationship between knowledge inertia and R&D team’s knowledge creation behavior, as well as exploring the leading and mediating role of organizational memory and the moderating role of R&D team’s innovative climate. After taking 135 R&D teams from 67 high-tech firms in Shenzhen as empirical research samples, the results indicate that: (1)Knowledge inertia will significantly destroy team's innovative climate, which will further negatively affect team’s knowledge creation behavior, as well as R&D team’s innovative climate plays a full mediating role in the relationship between knowledge inertia and team’s knowledge creation behavior; (2) R&D team’s organizational memory has no direct effect on team’s knowledge inertia, but will significantly moderate the relationship between knowledge inertia and R&D team’s innovative climate, that is, team’s organizational memory will not directly promote the generation of knowledge inertia, but will strengthen the negative impact of knowledge inertia on R&D team’s innovative climate.
In the new era, innovation capability has become the lifeline for enterprises to obtain and maintain sustained competitive advantages. With the progress of science and technology, society's demand for innovation is no longer limited to function and efficiency, but gradually turns to value and meaning. In this context, meaningful innovation (MI) emerged as an innovative paradigm that focuses on philosophical thinking and humanistic care. Based on the framework of meaningful innovation, this paper further focus on the innovation meaning asset (MA), as a higher-order resource, for an enterprise to obtain sustained competitive advantage in dynamic environment.
The speed of enterprise innovation has an important impact on the organization's competitive advantage. Based on the structural hole theory and human capital theory, this paper studies the influence of the structure hole position of the talent flow network on the innovation speed of enterprises. The empirical analysis results combined with LinkedIn online resume data and CSMAR show that there is a significant U-shaped relationship between the talent mobility network structure hole and the enterprise's innovation speed; the enterprise's internal absorptive capacity has a significant positive moderating effect on the relationship between talent mobility network structure hole and the innovation speed; while the market competition intensity has a significant negative moderating effect on the relationship between the two; further analysis found that the significant impact of structural holes on the speed of innovation mainly merely exists in non-state-owned enterprises. Further, we discuss the theoretical contributions and practical implications of this study.
Studying the systemic impact of domestic foreign capital knowledge spillover, reverse knowledge spillover, and domestic capital knowledge spillover on emerging economies will help to better understand the role of the knowledge spillover system in domestic innovation upgrade, and also will help to find breakthroughs in innovation. In view of this, our paper mainly designs three research contents: First, sort out the literature on triple knowledge spillovers and the innovation and upgrading of emerging economies, especially the discussion in the Chinese context; Second, describe the composition and evolutionary characteristics of China’s triple knowledge spillovers under the current international situation; On this basis, we deduced the overall characteristics of triple knowledge spillovers and the theoretical model of the connection between triple knowledge spillovers and domestic innovation upgrades, and tested the relationship between triple knowledge spillovers and the improvement of China’s overall innovation strength under the condition of heterogeneous samples.
This paper constructs a theoretical model to demonstrate the internal relationship between triple knowledge spillovers, and empirically tests the internal relationship between triple knowledge spillovers and domestic innovation upgrade under different sample conditions. The results show that: From the overall perspective, the total, direct and indirect effects of triple knowledge spillovers on domestic innovation upgrade are shown as positive promotion effects; From different perspectives, the combination of domestic foreign capital knowledge spillover and domestic capital knowledge spillover originating from the countries along the Belt and Road is positively promoting domestic innovation level in terms of the total effect, however, the direct effects of domestic foreign capital knowledge spillover and the indirect effects of reverse knowledge spillover are negatively correlated with domestic innovation upgrade; The total effect of triple knowledge spillovers originating from non-Belt and Road countries also has a positive effect on the promotion of domestic innovation, while the direct effect of reverse knowledge spillover is a suppression effect; All sample test results indicate that the technological gap between the knowledge spillover party and the knowledge receiver is beneficial to promote domestic innovation and upgrading, but the human capital gap between the two parties is negatively related to domestic innovation and upgrading.
According to the test results, management enlightenment for improving China’s innovation level can be obtained: First, in the context of the return of high-end Western capital led by the United States and the continuous deepening of the “Belt and Road” initiative, strengthen investment in technologically powerful countries and actively introduce intellectual capital from countries along the “Belt and Road” initiative; Second, focus on cultivating China’s human capital, both quantity and quality. Our research shows that the more obvious the gap between domestic human capital and foreign human capital, the less conducive to China’s innovation and upgrading; Third, give full play to the government’s guiding function to stimulate the vitality of Chinese companies’ exchanges and interactions and the potential for targeted R & D.
Based on the ego-network perspective of social network theory, this study chooses the enterprise alliance data during 2009-2016 as the research sample. This paper explores the impact of network closure on enterprise innovation performance and analyses the mediating and moderating effects of knowledge flow and knowledge diversity. Results from negative binomial regression method show that: the network closure has an inverted U-shaped effect on enterprise innovation performance; knowledge flow plays a partial mediating role in the relationship between network closure and enterprise innovation performance; knowledge diversity could weak the inverted U-shaped relationship between the network closure and enterprise innovation performance.
