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Disciplinary distribution of China’s research outputs: Evolutionary patterns and contributing factors Li Ning 2019, 40(1): 1-11.  Abstract ( 293 )   Although China as a transition country has evolved into the world’s second largest in both size of economy and number of academic publications, the nation has yet to gain the world’s leading position in scientific research. Whereas there is abundant literature assessing China’s national research capacity, most studies have focused on quantity of research outputs, often measured by the total number of publications or citations, while relatively less attention has been paid to the disciplinary structure of research outputs, often measured by the distribution of publications or citations across scientific fields. Thus, it is imperative for China to have a holistic and in-depth understanding of its disciplinary profiles (such as areas of relative strength and weakness), as it is key to the nation’s science policy-making, especially to the strategic planning for resource allocation in research.  The present study follows the tradition in bibliometric studies to trace and analyze the evolutionary patterns of China’s national research capacity in its disciplinary structure.  Particularly, it sheds lights on the major characteristics of China’s national disciplinary structure in research as compared to the world’s major scientific producers, as well as to the global research profiles and investigates whether there is a continuous pattern of convergence or divergence in China’s disciplinary structure towards the global research profiles.  Furthermore, this paper aims to advance the understanding of such evolutionary patterns through a historically oriented approach by taking into consideration social, institutional, economic, and policy changes over the history.   The dataset used by this study is extracted from the Scopus database covering 4 main areas (physical, life, health, and social sciences) and 27 major disciplines for the period from 1996 to 2015. Percentage distribution of publications across scientific fields is used for comparison of disciplinary structure between nations. The Finger-Kreinin Similarity Index (FKSI) is used as an indicator of the structural similarity between China’s academic publications as compared to the global distribution of publications. The level of specialization for each discipline is measured by the Relative Specialization Index (RSI). Significance of the structural changes over time in China’s disciplinary structures is tested through simple regression models.   It is found that China differs significantly from the world’s major nations in their research output distributions.  The rankings of China’s disciplinary specializations have been very stable, demonstrating consistency in its peculiarities and preferences. For example, China has constantly been comparatively strong in all major fields of physical sciences but weak in areas of life, health, and social sciences. Analysis of evolutionary patterns shows that there has been a continuous converging process of the disciplinary distribution between China and the world’s research outputs. The regression results reveal that this converging process has led to significant structural changes in China’s research profiles. However, the structural changes have been incremental overall. China has not reached the level of a balanced distribution compatible with other major research powers.   The author argues that the persistency in China’s disciplinary structure can be largely explained by path dependence processes jointly resulting from national strategies, S&T guiding principles, institutional settings, national culture, and historical events, among other contributing factors. First, following the nation’s development strategies, much of China’s R&D resources (best-trained personnel and ample funding) have historically been channeled into fields related to national security and defense, and a significant portion of research has been devoted to the national survey of natural resources. Second, guiding principles of China’s science policy revealed in a series of national science and technology development plans since the 1950s have had a consistent emphasis on prioritized fields, although recently with a gradual and steady shift towards an overall enhancement in the nation’s sustainable innovative capacity. Third, the imbalance between physical sciences and life sciences has been reinforced by China’s institutional arrangements, i.e. the composition of the members of the Academy of Sciences (CAS) and the disciplinary distribution of government research institutes. Fourth, historical events matter.  Research in life sciences and social sciences was largely damaged through political events, such as the dominance of Lysenkoism on China’s genetics and the discontinuation of sociology programs in universities. In the meantime, physical sciences were strengthened through the so called “Four Emergency Measures” (radio electronics, automation, semiconductors and computers) laid out in the 1956 Twelve-year Science and Technology Plan.  Fifth, values and norms in China’s national culture tend to favor incremental over radical changes.  This paper suggests that the above path dependency be overcome by effective implementation of science policies that encourage a more balanced distribution of research resources and industrial policies that stimulate the development of economic sectors related to pharmaceuticals and public health, which will in turn push research in life and health sciences. Related Articles | Metrics

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A research on measurement of the dynamic relationship of "science-technology-economy" output in China based on the perspective of "science-technology" interaction Chen Yue, Song Chao, Xu Fang 2019, 40(1): 12-21.  Abstract ( 162 )    Understanding correctly the relationship among science, technology and economy, and grasping the law of interaction between science and technology and economic development have an extremely important theoretical and practical significance. In fact, a large number of studies usually concentrate on the relationship among science, technology and economy independently, but they do not pay enough attention to the relationship between the “scientific & technical” interaction and economic development. Based on this background, this paper stands at the perspective of the separation of science and technology firstly, and uses the method of Granger causality test to explore the relationship among science, technology and economy. Then from the perspective of the interaction between science and technology, this paper uses the expanded Cobb Douglas production function, vector autoregressive model, impulse response function and variance decomposition method to measure the dynamic relationship of science, technology and economy output in China and demonstrate between the “scientific & technical” interaction and economic development. The scientific output data of this research comes from the Web of Science database and the Chinese CSCD database, and the technical output data comes from the China Statistical Yearbooks on Science and Technology (1991-2017), and the economic output data comes from the China Statistical Yearbooks(1991-2017), and the interaction between science and technology is obtained by product term of them. The conclusions show that scientific output is the Granger cause of technical output, and technical output is also the Granger cause of scientific output. It means that scientific output and technological output can promote each other. Scientific output is the Granger cause of economic output, but technical output is not the Granger cause of economic output. Compared with technological output, scientific output can better promote economic output. Economic output is not the Granger cause of scientific output, but in the long run, economic output is the Granger cause of technical output. Economic output promotes technical output better than scientific output. Further, the “scientific & technical” interaction is the Granger cause of economic output, but economic output does not constitute the Granger cause of the “scientific & technical” interaction. It shows that the “scientific & technical” interaction effect exists, and it plays an important role in promoting economic output. The economic development situation also has an important and unstable impact on the realization of the “scientific & technical” interaction effect. Related Articles | Metrics

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A research on the influence of organization distance and knowledge flow on radical innovation of strategic alliance enterprises Yin Hang, Zhang Yuhan, Liu Jiaxin 2019, 40(1): 22-31.  Abstract ( 375 )   Under the background of the rapid development of market economy, strategic alliance enterprises have been paid more attention by enterprises in the form of resource sharing and knowledge learning. The technological distance and social distance between strategic alliance enterprises have a direct impact on the knowledge flow within the alliance and the emergence of enterprise’s radical innovation. Enterprises and their own knowledge protection ability have a certain impact on the efficiency of knowledge flow between different organizations and enterprises and the success of radical innovation. Therefore, it is significance to clarify the impact of organizational distance between strategic alliance enterprises (including technological distance and social distance), knowledge flow (including knowledge acquisition and knowledge leakage), and knowledge protection ability on the radical innovation of alliance enterprises to promote the continuous realization of new breakthroughs by enterprises.This paper firstly defines and analyzes the relevant theories and concepts of organizational distance, knowledge flow, radical innovation and knowledge protection abilityamong strategic alliance enterprises based on the literature review at domestic and abroad. The organizational distance is divided into two dimensions of technical distance and social distance, and the knowledge flow is divided into two dimensions of knowledge acquisition and knowledge leakage. Then proposes seven groupsof hypotheses: H1a: The farther the technological distance is, the more favorable it is for alliance enterprises to make radical innovation. H1b: The closer the social distance is, the more favorable it is for alliance enterprises to make radical innovation. H2a: Knowledge acquisition positively influences the radical innovation of alliance enterprises. H2b: Knowledge leakage negatively affects the radical innovation of alliance enterprises. H3a: The farther the technology distance is, the more conducive it is to knowledge acquisition between alliance enterprises. H3b: The more distant the technology is, the less conducive it is to knowledge leakage between alliance enterprises. H4a: The closer the social distance is, the more conducive it is to knowledge acquisition between alliance enterprises. H4b: The closer the social distance is, the less conducive it is to knowledge leakage between alliance enterprises. H5a: Knowledge acquisition will mediate the relationship between technological distance and radical innovation. H5b: Knowledge acquisition will mediate the relationship between social distance and radical innovation. H6a: Knowledge leakage will mediate the relationship between technological distance and radical innovation. H6b: Knowledge leakage will mediate the relationship between social distance and radical innovation. H7a: Knowledge protection ability negatively regulates the relationship between knowledge acquisition and radical innovation. H7b: Knowledge protection ability negatively regulates the relationship between knowledge leakage and radical innovation.Next, on the basis of exploring the correlation between the variables of each dimension,a research hypothesis was proposed, and the conceptual model with joint action and knowledge protection ability as the moderating variables was established. The object of this study is strategic alliance enterprises in China. In order to ensure the accuracy of measurement, mature scales studied in relevant fields at home and abroad were selected as far as possible, and the expressions used in Chinese literatures were used for reference in the classical scales in foreign literatures. On this basis, improvements were designed. Before the formal investigation, 100 domestic enterprises were randomly selected as samples to issue the questionnaire. Based on the feedback results, the questionnaire was further improved and the final questionnaire was determined. From July to August 2017, 774 questionnaires were officially issued, 471 of which were valid, with an effective rate of 60.85%.The surveyed enterprises are evenly distributed geographically, most of them have been established for more than 6 years, and most of the respondents are senior managers. The survey is representative to some extent. Finally,in order to answer the question of how the organizational distance of alliance enterprises under the knowledge protection capability and the knowledge flow between them can promote the radical innovation, as well as the regulating role of knowledge protection capability. Based on knowledge management theory and resource-based theory, this paper proposes 7 sets of hypotheses and uses data from 471 strategic alliance enterprises to test the hypotheses. The results show that: (1) The technological distance and social distance between strategic alliance enterprises are conducive to the radical innovation of alliance enterprises. A certain technical gap and intimate relationship between partners within the alliance can help each member integrate the internal knowledge of the alliance with the enterprise’s own knowledge so as to develop new products and technologies. (2) The knowledge flow in the organization innovation breakthrough type in relation to the distance of partial intermediary role, in the league has different technical levels and the relationship of the cooperative enterprise will continue to increase the knowledge acquisition of internal finally realize its own radical innovation, but also can leak by lowering their own knowledge, the uniqueness of protection applied in the innovation of core knowledge, promote the breakthrough "innovation and development. (3) The knowledge protection ability of enterprises will weaken the negative effect of knowledge leakage on radical innovation, but it will not significantly weaken the promotion effect of knowledge acquisition on radical innovation.The research conclusion of this paper has a guiding significance for alliance enterprises radical innovation, through the organization of distance, knowledge flow and radical innovation three relations research, guide enterprises in selecting the appropriate technology gap in the league and close partners, promote the union both knowledge exchanges, mutual benefit and win-win results, a radical innovation and sustained development. Secondly, the analysis of the results of knowledge flow can guide enterprises to correctly view the different forms of knowledge flow within enterprises in the process of cooperation, and make full use of the positive role of knowledge leakage while acquiring and creating new knowledge to achieve radical innovation. Finally, according to the relevant research conclusions, it guides strategic alliance enterprises to continuously enhance their knowledge protection ability in the process of cooperative development, and promotes the application of property rights and institutional mechanisms in the field of enterprise knowledge protection in enterprise practice. Promote the mutual promotion of organizational distance, knowledge flow and radical innovation within the alliance, realize the common development of the alliance enterprises, and constantly create new competitive advantages to achieve sustainable innovation and development. Related Articles | Metrics

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An evolution from individual absorptive capability to organizational absorptive capability by taking knowledge sharing as mediator Zuo Bo, Zhang Wei, Wang Chen 2019, 40(1): 32-41.  Abstract ( 307 )    How the absorptive capability elvoves from the individual level to the organizational level has always been the focal point in the field of mangement. The concept of absorptive capacity was first proposed by Cohen and Levinihal in 1990. The core of absorptive capacity is to reveal how enterprises acquire, assimilate, transform and utilize external knowledge. As an important dynamic capability of an enterprise, this concept has been widely used to explain the complex problems in macro-strategic formulation and micro-product innovation. According to Cohen and Leviniha, On the one hand, the absorptive capacity of enterprises depends on the individual absorptive capacity; on the other hand, it is not equal to the simple accumulation of individual absorptive capacity. Firstly, absorptive capacity originates from the individual in the enterprise, which is the starting point of the absorptive capacity of the organization; secondly, only by evoving the absorptive capacity from individual level to the organization level, can it have more theoretical value and practical significance. Although this issue has drawn attention since it was put forward, Volberda et al. (2010) have reviewed the research literature in the field of absorptive capacity and found that there is still no clear explanation on how absorptive capacity is formed from the interaction between individuals and organizations.The revelation of the above problems is not only of theoretical contrubutions, but also of great practical implications. Over the past 20 years, a number of Chinese local enterprises have begun to rise. As Chinese local enterprises, especially emerging enterprises, are in a weak and backward state, and they are facing double disadvantages of technology and market. It is an important innovation strategy for many Chinese local enterprises to achieve innovation catch-up by acquring and assimilating external knowledge. For example, although Huawei is a high-tech enterprise with strong innovation capacity, it does not adhere to original innovation, but actively advocates minimizing its own invention and creation in the process of innovation, emphasizing on focusing on the technological achievements of previous products and the absorption of external knowledge and technology. On the issue of how to improve the absorptive capacity, many enterprises are facing the paradox of individual-organization duality at the practical level. The core problem is how to upgrade the absorptive capacity of individuals with independent behavior preferences to organizational absorptive capacity through effective organizational management mechanism.How does individual absorptive capacity evovle to organizational absorptive capacity? Past studies have explained it from the perspectives of organizational structure, incentive mechanism and network structure. Unlike these relatively static perspectives, we adopt the view of inter-subject interaction to reveal this issue, and believe that inter-subject knowledge sharing is a mediator of the evolution from individual absorptive capacity to organizational absorptive capacity. This theoretical presupposition is based on Habermas’s theory of communication and action. Its core view is that only through communication and interaction among the subjects, can a certain social consensus be reached and knowledge binding on all participants be formed. We believe that when there is consensus among the subjects and collective constrained knowledge is formed, knowledge memory at the organizational level can be formed, thereby promoting individual absorptive capacity to move beyond the threshold of "ego" to a more macro organizational level. At the same time, the degree of organizational centralization affects the digestion and utilization of knowledge at the organizational level. Knowledge exchange platform based on information technology and organizational common vision affect knowledge sharing among individuals. As the influencing factors of organizational knowledge absorption and individual knowledge sharing, they will affect the dynamic evolution absorptive capacity from individual levels to organizational levels.To test the above theoretical assumptions, this paper applied the empirical research paradigm based on the data from 275 enterprises. The empirical results indicate that knowledge sharing among individuals mediats the effect of absorptive capacity in individual level on absorptive capacity in organizational level. The empirical results also show that knowledge exchange platforms and shared organizational vision positively affect knowledge sharing among individuals, and the degree of centralization of organizational decision-making negatively affects organizational absorptive capacity.By studying the evolution from individual absorptive capability to organizational absorptive capability, this paper aims to make several contributions. Firstly, this paper reveals the evolution mechanism of absorptive capacity from individual level to organinzation level with the mediating effects of inter-subject knowledge sharing. The duality between individual and organization is the basic problem in the field of organizational learning and knowledge management. As Nonaka pointed out, how individual knowledge rises to organizational knowledge is the core of knowledge management research. As for absorptive capacity, revealing the evolution mechanism of absorptive capacity from individual level to organizational level is not only a basic theoretical issue in the field of absorptive capacity, but also of great practical values.An important theoretical contribution of this study is that this paper confirms inter-subject knowledge sharing mediating the process of the absorptive capacity evolution from individual level to organizational level. Secondly, this paper reveals the mechanism that the cross-level evolution of absorptive capacity is affected by different levels of factors. In the individual level, knowledge exchange platforms and the common vision of organizations have positive effect on the knowledge sharing among individuals. At the organizational level, the degree of centralization of organizational decision-making negatively affects the absorptive capacity of the organization. This paper uncovers the antecents of inter-individual knowledge sharing and organizational absorptive capacity, which contributes to the studies of absorptive capacity.Finally, this paper reveals the effect mechanism of organizational absorptive capacity on product innovation performance. Zahra and George differentiate the absorptive capacity into potential absorptive capacity and realized absorptive capacity. Potential absorptive capacity is a kind of knowledge accumulated capacity for enterprises, and the knowledge resources provides knowledge assets for enterprise product innovation. Realized absorptive capacity emphasizes the enterprises’ capacity of knowledge transformation and utilization. The stronger is the realized absorptive capacity, the stronger is the capability of enterprises applying knowledge resources to conduct R&D activities for innovation; thus,the better is the promotion of product innovation performance. Related Articles | Metrics

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Direct technological spillovers and regional independent innovation——An empirical analysis of Guilin City Zhang Jianqing，Liu Nuo， Fan Fei 2019, 40(1): 42-51.  Abstract ( 185 )   Endogenous growth theory holds that the technological progress is the motive force for a country’s sustainable economic growth. Technological progress, however, is often the result of the transfer of foreign innovative technologies, rather than its own R&D. This conclusion is particularly applicable to developing countries. Will this same path, namely the advanced technologies can be transferred from developed countries to developing ones, be followed within China’s different regions?The channels of technology transfer are international trade, FDI and direct spillovers. If there exists technological spillover between the eastern area and central and western areas in China, we assume that spillovers are generated through domestic interregional trade, investment and direct channels, one-to-one corresponding to three ways of technology transfer among countries. This paper compares the influence mechanism of interregional trade, investment and direct technological spillovers on regional innovation by constructing R&D stocks calculation model, and takes Guilin, as well as its sources of technology-Beijing, Shanghai, Chongqing, Nanning-as an example to examine our assumption.Our reference model is from Coe & Helpman (1995). They performed regression of the total factor productivity (TFP) to domestic and foreign R&D stocks. On this basis, this paper replaces foreign R&D stocks with the R&D stock outside the region, and subdivides it into R&D stocks of interregional trade, investment and direct spillover. At the same time, it replaces the TFP in the original model with innovation as an explained variable, thus comparing the effect of three technological spillovers on regional innovative capability.First, we calculate four parts of R&D stocks inside and outside Guilin during 1995-2014. It shows that except for R&D stock of direct spillover, those of interregional trade, investment and its own, rise with fluctuations. Among the total R&D stocks in Guilin, the average share of independent part is only 0.147%, which is 362 million Yuan in 2013, only occupying 0.36% and 0.22% of independent R&D stocks in Beijing and Shanghai, and 16.28% compared to Nanning, its provincial capital. Guilin’s independent R&D resources are seriously inadequate, therefore technological spillovers from outside the region is particularly important. Its R&D stock of investment accounts for the largest proportion on total R&D spillovers (an average of 69.86%) and has increased year by year since 1997, which indicates that investment from other domestic areas has brought a large amount of advanced technologies, similar to the situation of China’s strategy of “exchanging market for technology” in the 1990s. The R&D stock of interregional trade, average share 29.99%, has reached 82.877 billion Yuan in 2013, which is 100 times higher than that of 1994. It fluctuates greatly, and has experienced sharp increase in 2001 and 2005. Moreover, the proportion of R&D stock of direct spillovers is very small, ranging from 0.002% to 0.012%, and its fluctuation is also intense. Although it has increased 79 times, a big number, in the past 20 years, its positive effect on Guilin’s technological innovation is still not obvious.Second, this paper uses VAR model to do time series analysis of regional technological spillover effect in China. The empirical analysis shows that the technological spillovers of investment from Beijing, Shanghai and Nanning to Guilin significantly promote its independent innovation ability. The coefficient of Nanning’s technological spillovers of investment is the largest, for every 1% increase in R&D stock of investment in the first-lagged stage, Guilin’s innovation ability increases by 4.018%. Meanwhile, the positive effect of technological spillovers of investment from Beijing and Shanghai on Guilin’s innovation can last longer period. As for Chongqing, its interregional trade with Guilin has a significant impact on Guilin’s innovation capability. The technological spillover of interregional trade increases 1%, Guilin’s independent innovation can be significantly improved by 6.225%, 1.589% and 1.751% respectively for the latter three periods.As a whole, the impact of technological spillovers from interregional trade on Guilin’s innovation is the most significant among the explanatory variables, first-lagged of which increases 1%, leading Guilin’s independent innovation to expand by 2.102%.The influence of direct technological spillovers is relatively small in the short term;1% increase in the second-lagged one enlarges the independent innovation capacity by 0.146%. However, the coefficient of the third-lagged is 0.710, which is significant at the level of 1%, indicating that direct technological spillovers can promote innovation step by step. Independent R&D also has a positive impact on Guilin’s innovation. The 1% increase of second-lagged independent R&D will make its innovation rise by 0.434%. However, the contribution of technological spillovers of investment to Guilin is not significant. The first-lagged and second-lagged investment spillovers have negative impact on Guilin’s independent innovation, while the third-lagged one is positive but not significant.This paper then uses impulse response function to analyze further the dynamic interaction of technological spillovers from different channels on Guilin’s innovation. It found that direct technological spillover remarkably improves self-innovation in Guilin in short term, while it presents negative effect in the long run; the impact of technological spillovers through interregional trade on Guilin’s independent creation is stronger than direct technological spillovers; but the spillovers through investment do not increase the level of Guilin’s independent innovation. Moreover, the independent R&D in Guilin has an elevated function on its innovation that lasts longer period, although this contribution is less than that of interregional trade and direct technological spillovers.In conclusion, as direct technological spillovers have timeliness, we should constantly narrow the differences in TFP and the level of tertiary industry development within China’s different regions, strengthen personnel mobility and scientific research cooperation, enhance the absorptive capacity of central and western regions, thus help to continuously promote direct technological spillovers from developed areas to developing ones. Next, we should attach great importance to the interregional trade, especially increasing the import share of intermediate inputs and high-tech products from developed regions, and encourage interregional university-industry cooperation. At the same time, the independent R&D in the central and western regions should not be neglected. 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Impact of resource bricolage and R&D team’s impromptu creation on the new product development performance of startups Zhou Jianming, Zhang Xinsheng, Zhou Yongwu 2019, 40(1): 52-60.  Abstract ( 255 )    The role of bricolage that helping new established enterprises get resources to develop new product was examined in Chinese new established high-tech enterprises. Data from a survey of 133 R&D Groups with structural equation model method were applied to test a model proposing that bricolage to influence R&D group's improvisation, and so promote their new product development performance. We found that bricolage with resources recombination for new purposes not only took direct positive effect on new product development performance of entrepreneurial enterprises, but also took indirect positive effect on it through R&D group's cognitive and behavioral improvisation. At the same time, although bricolage with resources making do and bricolage with resources at hand took no direct effect on new product development performance of entrepreneurial enterprises, bricolage with resources making do can impact on it through R&D group's behavioral improvisation, and bricolage with resources at hand can impact on it through R&D group’s cognitive and behavioral improvisation. In addition, R&D group’s cognitive and behavioral improvisation both took direct positive effect on new product development of entrepreneurial enterprises significantly. Finally, implications of the findings were discussed. Related Articles | Metrics

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An evaluation of innovation capability of cliques and liaison firms Zhao Yan, Han Xiao, Li Zheng 2019, 40(1): 61-75.  Abstract ( 261 )   For the last few years firm alliances have been dramatically growing up and the competition pattern between individual firms has been transformed into a competitive pattern among cliques. Clique is a special structural unit in the meso-perspective network structure, which has become an important driving force for global high-tech firms to carry out cross-domain integration. The different cooperation patterns, cooperation degrees and participant types among the firms within the cliques play an important role in firms’ innovativeness, and they have a knock-on effect on the firms that are outside the cliques in the cognitive, strategic decision-making and innovation performance, etc. If a firm selects a wrong cooperation pattern or an inappropriate partner, it may face the threat of opportunistic behavior or disclosure of technical secrets. Previous research has examined the effects of network structure on the firms’ innovativeness. However, there is little work on the relationship between the type of cliques and firms’ innovativeness, and the cooperation mechanism among firms within cliques in alliance innovation network. In this paper, we focus on the relationships between clique types and firms’ innovativeness based on the theory of social network, and we propose a new method for clique classification in terms of non-structural attributes. Furthermore, cliques can be classified into nine types by their location in the value chain, cooperation patterns, and participant types. Based on different location of the value chain, cliques can be divided into R&D Cliques, Marketing Cliques, and Production Cliques. According to cooperation patterns, cliques can be subdivided into Informal Cliques, Contractual Cliques, and Equity Cliques. In terms of participant types, cliques can be classified into Government-led Cliques, Industry-University-Research Cliques, and Commercial Cliques. In addition, we introduce a new concept of node as Liaison Firm whose network location is among cliques. Finally, we measure the Cliques Segregation and Cross-cliques Convergence of the alliance innovation network to reveal the status of cliques’ development and the degree of high-tech industry convergence. Building on the literature on Cliques and firm’s innovativeness, we posit five hypotheses concerning how different types of clique and Liaison Firms affect firms’ innovativeness. Hypothesis 1 claims that Contractual Cliques are more conducive to firms’ innovativeness than Informal Cliques and Equity Cliques; Hypothesis 2 claims that Contractual Cliques are more conducive to firms’ innovativeness than Marketing Cliques and Production Cliques; Hypothesis 3 claims that Government-led Cliques, Industry-University-Research Cliques, and Commercial Cliques all have positive effects on firms’ innovativeness; Hypothesis 4 claims that Liaison Firm has a negative impact on firms’ innovativeness; and Hypothesis 5 claims that Liaison Firm plays a negative moderating role in the relationship between nine clique types and firms’ innovativeness.We constructed a firm alliance database that covers several Chinese high-tech industries over the period 2010-2015. Choosing firm alliances from nine high-tech industries made it possible for us to test the hypotheses including Semiconductors Industry, Automobile Body and Parts Industry, Chemistry and Chemical Industry, Aircraft and Aerospace Equipment Industry, Computer Video-audio Industry, New Energy and Environmental Protection Industry, Information and Communication Equipment Industry, Medical Equipment Industry, Pharmaceuticals and Biology Industry. The measures of the firm’s innovativeness bases draw on patent data from China Intellectual Property Net and the INNOJOY website. In addition, because our dependent variable is a count variable with a high degree of variance relative to its means, we use negative binomial regression analyses with random effects to demonstrate these hypotheses.The findings show that most of the cliques are isolated from each other in the network of the nine Chinese high-tech industries and Cross-cliques Convergence is also relatively low, which means high-tech firm alliances are in a relatively closed network environment In addition, the influence of different clique types on firms’ innovativeness is extremely diverse, and Liaison Firm does not have any rich resource advantages compared to other nodes in the alliance innovation network. The specific findings of our empirical research are as follows. Firstly, hypothesis 1 is strongly supported: since R&D Cliques have a positive effect on firms’ innovativeness. However, both Marketing Cliques and Production Cliques don’t show any influence on firms’ innovativeness. Secondly, hypothesis 2 is also strongly supported: because Contractual Cliques have a positive effect on firms’ innovativeness but Equity Cliques show a negative impact on firm innovativeness. Furthermore, there is no support of any relationship between Informal Cliques and firm innovativeness. Thirdly, hypothesis 3 is weakly supported: since there is only Commercial Cliques have a positive effect on firm innovativeness. Unexpectedly, Government-led Cliques have a negative impact on firm innovativeness, and Industry-University-Research Cliques don’t have any influence on firms’ innovativeness. Finally, Hypothesis 4 and Hypothesis 5 are strongly and weakly supported respectively: because Liaison Firm has a negative impact on firms’ innovativeness and plays a negative moderating role in the relationship between the Commercial Cliques and firms’ innovativeness but it does not show any moderating effects on the other two clique types and firm’s innovativeness.This work contributes to a new perspective on the classification of cliques in terms of non-structural attributes and puts forward a new concept of “Liaison Firm”. The results show that the firms’ innovativeness can be evaluated and predicted by the features of the innovation network, such as the Cliques Segregation, Cross-cliques Convergence. Further, we argue to understand how cliques affect firms’ innovativeness, it is necessary to disaggregate these cliques into different types, and it is also important to consider the Liaison Firm and network environment, which may have an effect on the firm’s innovativeness. Our findings also provide references for firms on how to select a win-win alliance partner, an advanced innovativeness clique, and a good position in the alliance network to enhance their innovation performance. In this way, our study suggests that firms should be embedded in the cliques that have advanced innovativeness, such as Contractual Cliques, Commercial Cliques, and R&D Cliques in view of the closed alliance innovation network environment in the nine high-tech industries of China and Liaison Firm should be embedded in relatively open cliques to avoid the risk of "Keep a Foot in Both Camps, Lose Trust on Both Sides". Related Articles | Metrics

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Influence of channel learning on innovation ability from the perspective of organizational inertia Fu Xiaorong, Luan Rui, Pang Jing 2019, 40(1): 76-88.  Abstract ( 389 )   Marketing channels are facing with major changes. In this context, how channel enterprises improve their ability to cope with the environment through learning is an important question that marketing management needs to answer. Organizational learning activities are divided into exploratory learning and exploitative learning. Do these two learning activities have the same effect on innovation ability? In particular, channel members learn from each other on the basis of long-term cooperative relationships, but long-term relationships also have a dark side. Organizational inertia can be divided into Structural inertia and Cognitive inertia. In the channel relationship, structure inertia is expressed as the relationship inertia, it refers to the organization members are locked in the existing relationship, is not willing to invest time and money to establish a new relationship. People with high relationship inertia tend to focus on relationships in their social circle and are less willing to face the risk of breaking up relationships. External information and opinions are filtered to inhibit members' ability to discover new problems. Cognitive inertia is manifested as intellectual laziness. According to the path dependence theory, organizations in stable relationships tend to maintain the status quo and do not accept new things outside the current strategy framework. This inertia is known as knowledge inertia. Knowledge inertia has a negative impact on organizational management and will inhibit the ability of organizations or individual s to solve problems. So what role does this dark side play in channel learning? This paper studies the influence mechanism of channel learning on innovation ability and discusses the mediating effect of organizational inertia and the moderating effect of ambidextrous learning on innovation ability. This paper uses SPSS20 and SMARTPLS3.0 to empirically analyze the questionnaire data of channel managers of 234 small and medium-sized enterprises. The results show that: (1) channel ambidextrous learning has a significant impact on innovation ability; Organizational inertia plays an intermediary role between channel ambidextrous learning and channel innovation. (2) channel learning has a two-way influence on the improvement of innovation ability; There are significant differences between relational inertia and knowledge inertia in the influence process between ambidextrous learning and organizational innovation: exploratory learning overcomes organizational inertia and is conducive to the improvement of innovation ability; exploitative learning to strengthen the inertia of the relationship has a negative effect on the improvement of innovation ability; (3) ambidextrous balance plays a moderating role in the process of learning influencing knowledge inertia.These show that: firstly, channel ambidextrous learning significantly influences innovation ability. Different from the existing researches on organizational ambidextrous learning, the focus of the existing researches is mostly intra-organizational ambidextrous learning, while the channel ambidextrous learning studied in this paper is a kind of inter-organizational ambidextrous learning with long-term relationship. It is found that two kinds of learning activities have different influences on innovation ability: channel exploration learning promotes innovation ability, while channel exploitative learning reduces innovation ability; and the more balanced ambidextrous learning is, the more it can overcome knowledge inertia and promote innovation ability. This conclusion not only extends the application scope of ambidextrous learning theory, but also indicates that channel enterprises should pay special attention to the cultivation of ambidextrous learning behavior in practice and should not fall into a single learning mode. Channel organizations can seek breakthroughs in channel structure, organizational situation and other aspects, overcome knowledge inertia by sublimating old knowledge and exploring new ways, accept new information and learn new knowledge, and better keep up with the pace of the market in the context of “artificial intelligence” era.Secondly, organizational inertia plays an intermediary role in the influence of channel ambidextrous learning on innovation ability. Channel ambidextrous learning is conducive to overcoming organizational inertia, which in turn inhibits innovation. The research shows that channel enterprises can reduce inertia (knowledge inertia and relationship inertia) through exploratory learning to improve their innovation ability. But the exploitative learning activities to overcome the inertia of knowledge at the same time also strengthened the inertia of the relationship, and thus adverse to the ability to innovate. This further reveals the influence mechanism of channel ambidextrous learning on innovation ability: the two kinds of learning activities have different influences not only on innovation ability, but also on the process. Therefore, when channel enterprises conduct ambidextrous learning, there may be two conflicting effects on the improvement of innovation ability caused by exploitative learning, and the indirect impact of exploitative learning on innovation ability depends on its influence on inertia (knowledge inertia and relationship inertia). In practice, channel enterprises can reduce organizational inertia by establishing learning team, learning organization and ambidextrous learning, so as to improve the innovation ability of the organization.Finally, most existing literatures believe that ambidextrous balance has a significant impact on innovation ability, but this study finds that: channel ambidextrous balance only plays a regulating role in overcoming knowledge inertia in channel ambidextrous learning; and when the two kinds of learning activities are highly unbalanced, channel enterprises can better overcome organizational inertia by combining high-intensity channel exploration learning with low-intensity exploitative learning, and thus perform better in innovation ability. This further explains the influence mechanism of channel ambidextrous learning on innovation ability and finds new boundary conditions of possibility for inter-organizational ambidextrous learning theory in the context of long-term relationship. More importantly, it also provides reference suggestions for channel enterprises when they need to balance between the two learning activities in actual business activities. Channel enterprises can reasonably allocate enterprise resources to carry out two kinds of learning activities within the organization, among channel organizations and in a balanced way, so as to overcome inertia, better respond to market changes and carry out channel innovation. In particular, in the actual operation process, when channel enterprises cannot achieve the balance of ambidextrous learning due to the limitations of their organizational structure, resource allocation and development stage, it is more advantageous for channel enterprises to focus on exploratory learning activities for their innovation ability.These research conclusions are beneficial to expand the research field of channel theory, supplement and improve the theoretical framework of channel research, and have certain guiding significance for channel members to improve their ability to cope with the highly changing market environment through ambidextrous learning. Related Articles | Metrics

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Identifying potential risks of 3D printing from the perspective of mining terms of trans-disciplinary areas 2019, 40(1): 89-104.  Abstract ( 210 )    In terms of the contemporary intelligent manufacturing (IM) and industrial Internet, three-dimensional printing (3DP) / additive manufacturing (AM) is definitely one of the most important key technologies because 3DP/AM can bring the disruptive innovation from high-level design to low-level manufacturing. Therefore, the academic topics about 3DP/AM attract more and more attention from many different kinds of scholars and institutes. While we retrospect the relevant publications on 3DP/AM during the past decades, we can find that most of the current research on 3DP/AM focuses on the huge innovation and market potential of 3DP/AM, and very few studies ever mentioned or touched the possible or potential risk of 3DP/AM. Actually, the main streams of studies on 3DP/AM just inform the very positive impact on economic systems, and very little is known about the possible/potential risk or threat to health, environment and ecology, security and social ethic and so on. Once 3DP/AM technologies would be popularized and industrialized, besides the tremendous pleasure for the emerging opportunities of economic development, the corresponding public-policies are also very important for the social-economic systems; otherwise, the emerging technologies could cause a new negative case of technology commercialization. However, the related studies and publications to the risk of 3DP/AM are still very few, and this exploration onthe risk of 3DP/AM are scattered in many different categories or academic areas, for example, chemistry, materials science, physics, biology and environment science and so forth. Obviously, because the risk signals on 3DP/AM are so weak and difficult to be identified and captured by those non-proficient policy-makers, a certain degree of information blockage and decision-making obstacles unintentionally derived, and the formulation of relevant policies on anticipatory governance has to face the difficulty of knowledge-acquisition. Further, the theoretical explorations and empirical analyses on the potential risk of emerging technologies are rare in the past decades, in particular the relevant quantitative studies on risk of a specific emerging technology almost keep blank; even could be a blind spot in the relevant areas on emerging technologies. To mitigate the gap between contemporary study on risk of emerging technology and concrete requirements of anticipatory governance and public policy making, a quantitative analytical method to identify the risk signal of a specific emerging technology is proposed, which can be attributed to a mining algorithm of cross-topic terms, and depends on the philosophy of nave machine learning. In the proposed framework of identifying the risk signals from the relevant publications on the observed emerging technology, the quantitative method can be divided into such different steps as: (a) the preparation of simple machine learning; (b) algorithm training based on a small sample; (c) the optimization of the relevant parameters. In each step, some concepts and computing equations are subsequently proposed. To verify the proposed identifying method for risk signals of emerging technology, the case study of 3DP/AM is conducted in empirical analysis. Relatively, the proposed method for identifying the risk of a specific emerging technology can provide moderate accuracy and recall ration, and significantly improve the efficiency of search the risk studies on a specific emerging to some degree. In terms of the empirical case on 3DP/AM, some important information is revealed and visualized that several significant risk or threat to human health and social security should be paid more attention in the contemporary stage of 3DP/AM development. First, several commercial polymer materials for 3DP in market present the biological toxicity that could make harmful impact on human health. Second, the ultrafine particles produced by 3DP/AM technologies not only bring the negative emission to the environment, but also bring the detrimental effect on human’s lung, in particular in the office space, and the harmful effect of ultrafine mental or polymer particles could cause unpredictable diseases. Third, the highly concentrated usage of power/electricity in 3DP/AM technologies could bring the huge impact on the stability of grid because the sintering steps in 3DP/AM rely on laser technology. In addition, 3DP/AM could aggravate the potential infringement of intellectual property because the technology of 3DP can make much easier copycats, and then could bring a big blow to those creative corporations and industries. Meanwhile, very few studies or researchers in social science can timely knew or responded to those risk signals of 3DP/AM, which could mean that the public concerns and public perceptions on 3DP/AM could be incomplete, i.e. the most of us just knew the huge potential for economic development about 3DP/AM, and very lack of the knowledge about the possible threats from 3DP/AM. In consequence, the relevant public-policies are highly possible time-lag, and even invalid while the health or security risk of 3DP/AM would become true events. China has the huge population, and very high density of population in some big cities; therefore, the potential or possible risk/threat of 3DP/AM or the other emerging technologies to human health, security and ethic should cause more attention from Chinese scholars, institutes and policy-makers because the loss in China or India could be much larger than the other small countries while those risk or threats of emerging technologies had really happened.However, the theoretical exploration and the empirical case on 3DP/AM also have limitations, for example, the mining method of trans-disciplinary topic terms has the room to enhance the accuracy, and whether the case study of 3DP/AM can be utilized by the other emerging technologies and so on. In addition, this paper just provides a new perspective to retrospect the prior studies on 3DP/AM, and does not imply the possible direction for the relevant researchers, i.e. how to encourage more scholars or institutes join the explorations on identifying risk signals for a specific emerging technology is not revealed by far.In view of the current scientific problems related to the identification and assessment of potential risks of emerging technologies, this paper proposes an interdisciplinary/trans-disciplinary topic word mining algorithm based on naive machine learning, and makes an empirical analysis with the current hot three-dimensional printing technology. Theoretical and empirical analysis show that the proposed method has a certain content recognition capability on the mining the potential risk signal for a specific emerging technology, which may have a certain value and positive significance for public governance decision-making and science and technology policy formulation for emerging technology. Related Articles | Metrics

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A research on the effect of competition from informal sector on firms’ innovation behavior Wen Huwei，Sun Yanlin，Zhou Fengxiu 2019, 40(1): 105-0.  Abstract ( 205 )   Most of the existing literature focuses on the scale change of informal sector from the macro level, while few pay attention to its impact on micro-enterprise behavior. Using micro-econometric model and the World Bank’s Enterprise Survey data from a sample of China, our paper addresses this issue. We study the impact of competition from informal sectors on innovation behavior of competition against producers in the informal sector. The empirical results show that the competition has a significant positive impact on the R&D investment, both in quantity and in intensity, which means the competition from informal sector will promote the innovation investment of formal firms. In terms of innovation types, the added resources are mainly used for activities such as updating product, upgrading technology and improving capacity of personalized production. However, there is no significant evidence suggesting the influence of competition on process innovation, which is always aimed at improving product quality and reducing production cost. In terms of innovation modes, the competition from informal producers will obstruct the independent innovation and promote the imitation innovation. Our government needs to regulate the unfair competition behavior of informal producers, and guide them to transform from informal producers to entrepreneurial organizations. Related Articles | Metrics

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Market orientation, resource bricolage and business model innovation 2019, 40(1): 113-120.  Abstract ( 302 )   The concept of marketing orientation is considered to be the cornerstone of strategic marketing, however, the effect of market orientation impact on the enterprise innovation has been controversial. Based on the Resources Constructivism Theory, this study based on the difference of responsive market orientation and proactive market orientation, from the perspective of resources bricolage, explore the relationship between market orientation and business model innovation. Research results show that: (1) the proactive market orientation has a significant positive effect on business model innovation, and responsive market orientation has a inverted U shape influence on business model innovation;(2) the proactive market orientation and responsive market orientation both have significant positive influence on resources bricolage;(3) resources bricolage played a partial intermediary role between proactive market orientation and responsive market orientation impaction on business model innovation, respectively. Related Articles | Metrics

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Network relationship strength, coopetition strategy and enterprise performance from the perspective of coopetition Wang Jianping, Wu Xiaoyun 2019, 40(1): 121-130.  Abstract ( 292 )   This paper started from the perspective of coopetition based on the value network theory by selecting 246 enterprises from the CSMAR database of Guotai’an as samples, and applies factor analysis, multiple linear regression and Bootstrap method to focus on the internal mechanism and action mechanism of the impact of network relationship strength on performance of Chinese enterprises in the context of value network. Different from the previous studies that regard competition and cooperation as the only unread ones, this study defines coopetition strategy as the competition and cooperation strategy within the two-dimensional framework, namely it divides and defines competition strategy and cooperation strategy from the two dimensions of competition and cooperation.The empirical study shows that: under the current situation of China, the strength of network relationship has a significant positive impact on enterprise performance, which is highly consistent with the cultural characteristics of Chinese human society; In the process of network relationship strength influencing enterprise performance, both cooperative strategy and competitive strategy play a mediating effect, and the mediating effect of cooperative strategy is obviously greater than that of competitive strategy, which indicates that cooperation occupies a dominant position in the relationship between enterprises. The difference within the network significantly strengthened the positive relationship between the strength of network relationship and cooperative strategy, but the moderating effect on the relationship between the strength of network relationship and competitive strategy was not significant.The above empirical results show that Chinese manufacturing enterprises constitute a complex network of relationships. From the point of view of network strength, it can be roughly divided into strong relation network and weak relation network. Under the strong network relationship, enterprises should adopt the mode of strategic allocation which is mainly cooperative strategy and supplemented by competitive strategy. In the case of weak network relationship, the opposite strategic configuration should be adopted. In addition, enterprises should pay special attention to the role and influence of differences within the network when applying cooperation strategies, because the uniqueness and complementarity of resources caused by differences within the network will profoundly affect the cooperative relationship between enterprises. At the same time, the conclusion of this paper also shows that there is no pure competition strategy and cooperation strategy in reality. Enterprises should change their concepts, abandon the view of competition and cooperation as a one-dimensional construct, and adopt the view of competition and cooperation as a two-dimensional construct with mutual influence and different emphases, so as to better grasp the balance between competition and cooperation. The above research conclusions have a positive guiding significance and theoretical value for Chinese manufacturing enterprises to adopt correct competition and cooperation strategies and continuously improve enterprise performance. Related Articles | Metrics

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Mitigation effect of TMT social capital on CSR negative events from the perspective of product market Liu Yuanyuan， Xu Peiyu， Liu Jingyu 2019, 40(1): 131-138.  Abstract ( 232 )   Frequent outbreaks of corporate social responsibility (CSR) negative events resulted in serious negative impact on enterprise performance. These negative events may be due to insufficient capacity of enterprises or lack of morality of enterprises. With the product market perspective being a key factor affecting enterprise performance, this paper uses multiple linear regression analysis to examine the impact of CSR negative events on the product market competitiveness and the mitigation effect of the top management team (TMT) social capital. The empirical results show that: CSR negative events significantly reduce the product market competitiveness; the morality-related negative events have stronger influence on the product market competitiveness than ability-related negative events; the CSR negative events have a more adverse effect on the product market competitiveness in the competitive industry than monopoly industry; and the TMT social capital can significantly alleviate the impact of CSR negative events on the product market competitiveness. The conclusions provide suggestions and support for management to cope with CSR negative events. Related Articles | Metrics

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A research on the mechanism for implementation of firms’ SCSR program Cheng Cong, Chi Renyong, Zhang Wei 2019, 40(1): 139-150.  Abstract ( 169 )   firm’s SCSR program which attempts to create value and promote social welfare to grow as the same time, it implies that how to push forward the SCSR program is a vital problem firm as much as society faced. Employing the object of exclusive car service business, such as didi taxi, kuaidi taxi and so on, growing up in main cities of China, and comparing the methods of case study and quantitative analysis, we found that strategic traits including goal orientation, marketing reaction, business benefit and reputation mechanism are emerging in the driving processing of SCSR program, this strategic traits are principal factors accelerating the SCSR program. In addition, there is a significance difference between different stakeholders assess the strategic traits. For the stakeholders emphasizing firm’s business benefit will pay attention to business benefit, goal orientation, reputation mechanism and marketing reaction decrease by degress decrease successively. However, the stakeholders emphasizing social welfare growing will pay attention to marketing reaction, business benefit, reputation mechanism and goal orientation decrease by degress decrease successively. This paper offer a positively proposal that how to promote the SCSR program successfully. Related Articles | Metrics

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An empirical study on the influence mechanism of reward for innovation on the innovative behavior of R&D employees Liu Ning, Zhang Zhengtang, Zhao Yanmei 2019, 40(1): 151-158.  Abstract ( 299 )   Behavioral theory and self-determination theory held different views on whether rewards had influence on employee innovation or not and on the process that rewards worked as well. They also had different empirical findings. Starting with behavioral theory, this study explored the effects of reward for innovation on the willingness to innovate and innovative behavior of R&D employees in Chinese context, as well as the moderating effect of materialism. Based on the paired data of 312 R&D employees and their supervisors, this study carried on an empirical study and tested the mediated moderation model. The results showed that reward for innovation had a positive effect on the innovative behavior of R&D employees. The willingness to innovate partly mediated the relationship. Individual’s materialism moderated the relationship of reward for innovation and the willingness to innovate. To employees with high materialism, the reward for innovation had a stronger effect on the willingness to innovate. Especially, the moderating role of materialism on the reward for innovation and innovative behavior was mediated by willingness to innovate. Related Articles | Metrics

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Internal social capital, ambidextrous learning and R&D team creativity Dai Wanliang, Yang Jiaoping, Li Qingman 2019, 40(1): 159-169.  Abstract ( 246 )   The main reasons for the insufficient innovation of the R & D team are the low enthusiasm and creativity of the team members, the knowledge communication and thinking collision of team members under good relationship are very important to the creativity of R & D team. This paper takes the ambidextrous learning as the mediating variable and the knowledge heterogeneity as the moderating variable, constructs the moderated mediating model of internal social capital affecting the R & D team creativity. Using the structural equation model, the empirical study based on the data of 308 R & D teams found that: firstly, the direct effect of structural capital and cognitive social capital on R & D team creativity is significant, while the direct effect of relational capital on R & D team creativity is not significant. Secondly, the ambidextrous learning plays a partial mediating role in the impact of structural capital and cognitive capital on R & D team creativity, while plays a whole mediating role in the relationship between relational capital and R & D team creativity. Thirdly, the knowledge heterogeneity is positively moderating the mediating effect of the ambidextrous learning. This study will helps to understand the influencing factors and mechanism of team creativity, and also provide a reference for improving the R & D team creativity. Related Articles | Metrics

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Lead user research:Concepts, measurements and influencing factors Wang Nan, Zhang Shikai, Chen Jin 2019, 40(1): 170-177.  Abstract ( 357 )   Studying lead users can understand future market development trends and capture user needs, develop new products and services with more market potential and so on, and increase the competitive advantage of the company's new products or services. But the relevant research is not yet mature, and domestic research is very scarce. Based on the relevant foreign language databases, this study sorts out the important results of theoretical research of lead user, and analyzes in depth the concept, scales, measurements, and influencing factors. Results show that: first, lead users are individuals that are at the forefront of trends in important marketplace (ahead on an important marketplace trend) and expect high benefit from obtaining solutions to their needs (high expected benefits); second, the scale includes two basic dimensions of ahead on an important marketplace trend and high expected benefits; third, the antecedents of lead user consist of field-related variables, field-independent variables and motivation. Finally, the prospect of future research is prospected in order to provide references for domestic scholars to further study lead users and enterprises cooperate with lead users in new product development. Related Articles | Metrics

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A research on the comprehensive influence evaluation of scholars under the integration of multidimensional measurement indicators by taking the gene editing field as an example Wang Feifei, Jia Chenran, Wang Xiaohan 2019, 40(1): 178-190.  Abstract ( 324 )   With the development of science and technology, scholars have become the main part of scientific research. Evaluating the influence of scholars is conducive to promoting the enthusiasm of scholar’s research, and can also provide reference for superiors to introduce outstanding talents. The influence of scholars reflects the academic level of scholars, and the screening of scholars with excellent comprehensive influence is helpful to promote the development of scientific research. At present, there are many indicators to measure academic influence, so it is very important to distinguish the applicable indicators. Structural equation model is used to select reasonable, significant and authoritative indicators from a variety of indicators. Meanwhile, it can measure the impact of indicators on various levels and identify the core indicators at different levels. Through the construction of structural equation model between academic literature influence, academic cooperation influence, academic citation influence, social influence and network community influence of scholars in the field of gene editing, it is found that academic track is the main measure indicator in the level of academic literature influence, which integrates the quantity of publications and the citation frequency, combines the traditional indicators, embodies the depth of scholars’ research from the aspects of quantity and quality, horizontal and vertical, and can be used to evaluate scholars’ performance. It is a new perspective to measure influence. It reflects scholars’ ability in many aspects. The impact factor more represents the level of journals in which scholars publish their papers, and this indicator has year limitations on citation statistics. Therefore, the representativeness is lower than other indicators. At the level of academic cooperation influence, citation intensity and degree centrality are the core indicators. Centrality is the most direct measurement indicator, indicating the status of nodes, citation intensity includes the quality of cooperation papers on the basis of cooperation frequency, revealing the cooperation influence of scholars from two perspectives, with strong representativeness. In the dimension of academic citation influence, PageRank value and degree centrality are important indicators. We can see that degree centrality occupies the main position in social network, and PageRank value takes into account both the quantity and quality of citations, which makes up for the drawbacks of some indicators and has certain authority.  At the level of social influence, Altmetrics-h index can identify high-level scholars more deeply. On the basis of Altmetric Score, the concept of h-index is synthesized to reflect the public’s recognition, belonging to the core indicators. In the influence of network community, the role of Researchgate_reads and Researchgate_follower is slightly higher, and more intuitive reflect the ability of online interaction. RG Score is also a important indicator, because it considers contribution, communication, reputation and other factors from multiple perspectives, and at the same time, combined with the degree of recognition by others, it represents the overall strength of scholars. Then the skyline algorithm is used to realize multi-dimensional comprehensive evaluation, identify talents that other scholars cannot surpass in many aspects. In the social media environment, there are many platforms that can reflect the influence of the network community. Researchgate platform has been rising in the academic circles and gradually gained the recognition of researchers, providing a more conducive channel for online communication. Although the Researchgate platform is well-known, there are some controversies in academic circles about the Researchgate platform. In order to determine whether the network community impact indicators represented by Researchgate are recognized and applicable to the measurement of scholars’ influence.  This paper evaluates the comprehensive influence of scholars in the field of gene editing by skyline algorithms from coverage and non-coverage of the influence of network community indicators two aspects, and analyses its effectiveness. The study found that 8 and 14 scholars were screened out from the coverage and non-coverage Researchgate indicators. The two situations are basically consistent, and some scholars have great turning points. The results are consistent with the actual promoters of the gene editing field research. Zhang Feng, Horvath Philippe, Mali Prashant, Koonin Eugene V, Van der Oost John, Jinek Martin are excellent scholars who have jointly measured. Zhang Feng, Horvath Philippe, Mali Prashant are all in the leading position except for the influence of the network community, which shows that they mainly focus on the performance of the literature level.  In addition, the evaluation system that covers the Researchgate index can help to select more outstanding scholars. In the model containing the Researchgate indicator, most scholars rank the top in the influence of the network community, which shows that the network communication ability is strong, and get the attention of multi-level people. Among them, Raoult Didier scholars are the most representative, and the influence of network community ranks first, but the other dimensions are relatively backward. In recent years, Raoult Didier has published thousands of different types of academic performance mainly in the Researchgate community, with strong dissemination ability, and constantly shifting from the traditional platform to the Researchgate community, reflecting the academic status from the perspective of network media. Other outstanding scholars selected include Church George M, Chylinski Krzysztof, Jinek Martin, Holmes Michael C, Gootenberg Jonathan S, Muramatsu Masamichi, Nemazee David and Sprengl Rolf, which have promoted the development of gene editing to some extent. It further proves that the Researchgate indicator is an important factor affecting scholars’ academic ability. It is useful for academic evaluation as a supplementary indicator, and the feasibility of establishing a multi-dimensional comprehensive evaluation system. In the environment of Web 2.0, social media platforms are becoming more and more popular. Research is no longer limited to traditional indicators, but gradually popularizes Altmetrics indicator, focusing on network interaction activities. This paper puts forward a new research idea through the integration of various categories of indicators to measure the influence of scholars from multi-dimension, which can be further popularized. To provide some reference for the expansion of scientific and technological evaluation theory and application practice, and promote the development of scientific research. Related Articles | Metrics

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A study of the multi-scale scientific collaboration patterns based on complex networks Liu Liang, Luo Tian, Cao Jiming 2019, 40(1): 191-198.  Abstract ( 252 )   The identification of the scientific collaboration network structure using network theory can help to understand the collaboration patterns and behavior mechanisms among scientific individuals. Applying with complex network multi-scale paradigm, the multi-scale network methods, i.e., marco-, mesco-, and micro-scale concepts, algorithms and applications for analyzing the global, module, and motif structure of the scientific collaboration networks were explored. Furthermore, these methods were effectively applied to reveal the multi-scale nework collaboratin patterns and behavior mechanisms of the real scientists’ collaboration network in the field of complex network research. The research may provide hierarchical ideas and methods for detecting, analyzing and managing the collaboration patterns and behavior mechanisms in complex scientific collaboration systems. Related Articles | Metrics

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Effects of extrinsic incentive and intrinsic motivation on college teacher’s research performance Liu Guang, Yu Huajun 2019, 40(1): 199-208.  Abstract ( 263 )   Exploring the mechanism of college teacher’s motivation effects on their research performance is very important for the innovation system of colleges research incentive. Through the 703 valid questionnaires from college teachers, the empirical tests of extrinsic incentive’s and intrinsic motivation’s effects on research performance are separately studied by using the path analysis of SEM (Structural Equation Model), based on the structural dimension analysis of extrinsic incentive and intrinsic motivation and research performance by EFA (Exploratory Factor Analysis). The results of EFA indicate as follows: 1. Extrinsic incentive includes salary incentive, evaluation incentive and promotion incentive; 2. Intrinsic motivation includes innovation motivation, achievement motivation, social motivation; and 3. Research performance includes process performance and result performance. The path analysis results are as follow: first, salary incentive, evaluation incentive and achievement motivation do not affect the process performance, while promotion incentive, innovation motivation and social motivation not only do but also further affect result performance by it. second, promotion incentive and social motivation do not directly affect result performance. Furthermore, salary incentive, evaluation incentive, innovation motivation and achievement motivation have the direct negative effects on result performance; and third, process performance(attitude and behavior) is the intermediate variable and key variable that can really make motivators work. The above results have certain reference value for the management reform of science research in Chinese colleges. Related Articles | Metrics