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Knowledge transfer is considered the efficient way to improve regional innovation, but relatively little is known about how the innovation efficiency of scientific and technological (S&T) talents is affected by knowledge transfer within institutional environment, particularly, limited studies carried out regional differentiation analysis. Using panel data from 30 provinces in China between 2005 and 2017, this article empirically tests the influence of the institutional environment on knowledge transfer and analyses its impact between knowledge transfer and innovation efficiency of S&T talents in China. The results show knowledge transfer can significantly improve both the scientific and the economic innovation efficiency of S&T talents. Moreover, the effects of knowledge transfer on the innovation efficiency of S&T talents in eastern, central and western China had heterogeneity. Formal and informal institutions play mediating roles between knowledge transfer and innovation efficiency of S&T talents. This study contributes to the literature by constructing an econometric model with identified variables to test the impact of knowledge transfer on the innovation efficiency of S&T talents in China, in addition, the equation about knowledge transfer was explored. The research findings are valuable to regional governments and policymakers; our empirical evidence helps to develop more efficient strategy and policy planning. [ABSTRACT FROM AUTHOR]

Foreign direct investment (FDI) technology spillovers play an increasingly important role in a host country's development. Evaluating the positive effect of FDI inflows on green innovation is essential for correct city design. Based on the panel data of 262 cities in China from 2004 to 2018, we first analyzed the impact of FDI technology spillovers on green innovation in Chinese cities and then tested the threshold effect in four absorptive capacity factors: environmental regulation, economic growth, human capital, and industry size. Finally, we compared the time and space of two types of cities crossing the threshold from the perspective of innovative and non-innovative cities. The results show that FDI can significantly promote green innovation in Chinese cities and the promoting effect of FDI on green innovation has nonlinear characteristics, namely, such effects only make sense when absorptive capacity is above the threshold points. Additionally, among the four absorptive capacity factors, the development degrees of innovative cities are ahead of non-innovative cities; in particular, there is a significant difference between them in terms of economic growth. Local governments should develop reasonable policy combination tools according to the absorptive capacity characteristics of different cities to effectively promote the technology spillover effect of FDI and achieve coordinated ecological and economic development. [ABSTRACT FROM AUTHOR]

Universities are important parts of innovation ecosystems, and university technology transfer (UTT), which aims for the sustainable commercialization of sci-tech achievements, is closely related to other actors in the ecosystem. Based on the panel data of 31 provinces in mainland China, this paper empirically analyzes the spatiotemporal distribution characteristics of UTT levels from 2011 to 2019 and estimates the influencing factors using the spatial Durbin model (SDM) with an economic spatial weighting matrix from the perspective of innovation ecosystems. The results are presented as follows: (1) Although the overall level of UTT in China is low, it shows an upward trend in most provinces. In addition, the interprovincial gap is obvious, forming a ladder distribution of UTT levels increasing from west to east. (2) There is a significant spatial autocorrelation between UTT levels in the provinces. (3) Industry, economy, and informatization play significant roles in promoting UTT, while financial institutes and openness have significant inhibitory effects. The economy has a significant spatial spillover effect on UTT, while government, industry and informatization have a significant inhibitory effect on UTT in neighboring regions. (4) The direct and indirect effects of influencing factors in the Eastern Region and other regions show significant spatial heterogeneity. [ABSTRACT FROM AUTHOR]

Interregional collaboration is a core element of Chinese innovation policy, as it accelerates the knowledge recombination across geographic boundaries and promotes regional R&D performance. This study emphasizes interregional collaboration and investigates its effect on R&D productivity using 2009–2017 panel data for 30 Chinese provinces. Furthermore, it examines the relationship between interregional research collaboration and interregional gaps of R&D productivity based on a multistage perspective. Our findings reveal that although interregional collaboration and R&D productivity in China constantly improved during the study period, there is to some extent a mismatch in their spatial distribution. We find that interregional collaboration is required to support overall R&D productivity. We also emphasize that interregional collaboration contributes more to narrowing the interregional gaps of knowledge productivity (rather than technology transfer productivity). [ABSTRACT FROM AUTHOR]

Innovation is intrinsically dependent on the construction of local infrastructure. Using panel data on 285 cities in China, we empirically examined the impact of high-speed rails on urban innovation and the mechanism underlying this effect. We found that high-speed rails significantly increase urban innovation. In our analysis, high-speed rails were found to increase the agglomeration of innovation factors, including population and investment, which in turn increase urban technological innovation. The agglomeration of investment factors brought about by high-speed rails is the main source of the improvement in urban innovation. Through the use of a spatial panel model, we found that high-speed rails promote knowledge dissemination and technology spillovers among the cities along high-speed railways, thus improving their innovation levels. However, the existing effects of high-speed rails on innovation exhibit spatial heterogeneity. We confirmed the effect of high-speed rails on innovation and explored the mechanism underlying this effect by considering the effects of factor agglomeration and knowledge spillovers. Our conclusions can be used as a resource by policymakers to stimulate knowledge and technology diffusion, which in turn cultivates and stimulates urban innovation. [ABSTRACT FROM AUTHOR]

As China's economy continues to grow rapidly, the importance of green and sustainable development is increasingly prominent. In this context, enterprises have undergone significant changes in all aspects of the value creation process. Based on the data of Chinese a-share listed companies from 2011 to 2021, this paper links the digital transformation of enterprises with the green technology innovation of enterprises. The focuses on the relationship between the enterprises' digital transformation and the enterprises' green innovation and its Local-neighborhood effect. Research shows that the digital transformation of enterprises will promote the enterprise green technology innovation, and this relationship will have a Local-neighborhood effect in different regions, and this spatial spillover effect is mainly achieved through the transfer of high-tech industries between regions. The results of heterogeneity test show that the effect of green technology innovation is the strongest in Beijing-Tianjin-Hebei economic circle, and the weakest in Pearl River Delta economic circle. Based on the spatial econometric model, this paper provides empirical evidence for the government and the state to formulate the regional development strategy of enterprises' digital transformation and green innovation. • Spatial panel Durbin model reveals digital transformation's impact on green technology innovation and regional spillover. • The effect of digital transformation of enterprises on their own green technology innovation has a "local-neighborhood" effect. • The spatial spillover effect is mainly realized through the transfer of high-tech industries between regions. • The strongest green technology innovation effect is found in the Beijing-Tianjin-Hebei economic circle. [ABSTRACT FROM AUTHOR]

The universities' scientific and technological activities have become the key link of science and technology and economy, and the core of promoting the national innovation capability and competitiveness. To achieve high-quality development of China's science and technology, it is of great significance to measure the efficiency of universities' scientific and technological activities accurately and explore their regional differences. Based on the innovation value chain, we construct a two-stage efficiency measure index system of universities' scientific and technological activity, and then according to the universities' statistical data in China from 2010 to 2017, by taking provincial universities as the research object, we exploit a two-stage network DEA model with shared input to measure the provincial efficiency of universities' scientific and technological activities in China; what is more, we explore the provincial differences in efficiency of universities' scientific and technological activities. Finally, we extract the influencing factors on the efficiency of universities' scientific and technological activities using the dynamic panel data model. The results show that there are serious problems in the transformation between knowledge output and results in the universities' scientific and technological activities. The scientific and technological activities of regional universities in China are not balanced. For provincial universities' efficiency of scientific and technological activities, there exist great differences among different time and space, stages, and resource utilization modes. The endogenous factors such as policy system and technology service are much more important factors. [ABSTRACT FROM AUTHOR]

The effect of technological innovation on renewable energy development has drawn attention from scholars and policymakers. Based on a panel dataset covering 30 provinces in China from 2005 to 2017, the present study aims to examine how renewable energy technological innovation (RETI), represented by patent stock considering the decay and diffusion of renewable energy technologies, promotes renewable power generation (RPG) by nonspatial and spatial econometric models. The results indicate that 1) a 1% increase in the RETI level of a particular province, on average, leads to a 0.411% increase in RPG in that province directly and a 3.264% increase in RPG in its neighboring provinces through technology diffusion; 2) the effect of RETI on RPG will be underestimated by 12.7% if the decay and diffusion of technologies are not considered; 3) the estimation coefficients of RETI are insufficiently sensitive to the values of the decay and diffusion rates; 4) spatial dependence plays a vital role in exploring the impact of RETI on RPG, and this impact will be underestimated by 34.3% if spatial dependence is ignored. • Renewable energy technological innovation (RETI) contributes to renewable power generation. • Indirect effect of RETI on renewable power generation is 8 times greater than direct effect. • Coefficients can be underestimated if technological decay and diffusion are not considered. • Effect of innovation is not sensitive to the decay or diffusion rates. [ABSTRACT FROM AUTHOR]

Latecomer technology imitation and learning is an important driving force to enhance their competitiveness and total factor productivity (TFP). This paper constructs green TFP (GTFP) based on the SBM–Global–Luenberger index, using Chinese provincial panel data from 2003 to 2017. The marginal effects of foreign direct investment (FDI), outward foreign direct investment (OFDI), import and export, and intangible and total international technology spillovers (ITS) on GTFP were assessed. These effects were analysed under the influence of absorption capabilities such as research and development intensity, economic and financial, and openness. A spatial diffusion model based on three diffusion sources in China's first-tier cities, Beijing, Shanghai, and Guangzhou, was constructed to describe the heterogeneous impacts of ITS on GTFP under the marketisation of diffusion sources. We found: (1) ITS based on exports and OFDI promote economic, imports and FDI are relatively small, independent technological innovation is the dominant source of economic growth. (2) Considering spatial diffusion, the contribution of Beijing's ITS is relatively weak, and Shanghai's contribution is stronger. Coastal areas have the largest marginal effect of ITS on GTFP, and ITS do not attenuate as geographic distances increase. (3) The market has a multiplier effect, modifying the relationship between ITS and GTFP. [ABSTRACT FROM AUTHOR]

Given the regionally differentiated environmental regulatory means, this paper evaluates the contribution of firms' R&D investment to economic growth with interprovincial panel data on 30 provinces in China from 2009 to 2016, which is based on the time-varying threshold model. Additionally, the coupling coordination degree model (CCDM) is used to measure the effects of technological innovation through enterprise collaboration for R&D input and investment-focused environment regulations. We then explore the inter-regional technology transfer path with different cooperation effects in areas and find: (i) The economic performance of the R&D investments of regional enterprises shows a downward trend with the strengthening of cost-focused ER while an inverted 'U'-shaped relationship that first strengthens and then weakens is presented with the strengthening of investment-focused ER. (ii) The degree of coupling calculated by CCDM is generally low, and synergies are improving from the west to the east, from a geographic perspective. [ABSTRACT FROM AUTHOR]

The innovation value chain is an effective tool for analysing innovation activities and reflects the process of value creation and increase in innovation activities. From the perspective of innovation value chains, we divided patent innovation activities into three stages: knowledge innovation stage, applied research stage and patent commercialization stage. The panel data from 64 universities directly managed by the Ministry of Education from 2009 to 2017 were used and several conclusions were drawn: 1) In the initial stage of knowledge innovation, the fundamental research fund plays a crucial promoting role, and knowledge innovation achievements are mainly published academic papers. 2) In the applied research stage, the knowledge innovation in the early stage and the fund investment in R&D activities have a significant positive effect on the patent output of universities, but the personnel investment has a negative effect. 3) In the final stage of patent commercialization, preliminary research results have a positive impact on patent commercialization, whose marginal effect depends on the industry-university-research relationship, external competition and reputation of the university. The evidence showed that there is a feedback channel between university patent commercialization and knowledge innovation, and new knowledge generated by the interaction with the outside world in the process of patent commercialization was transmitted to the subject of knowledge innovation through this channel, forming a virtuous dynamic cycle. By analysing the driving factors of the value chain of patent innovation in colleges and universities, we provided empirical evidence for the operation mechanism and policy formulation of college patents in China. [ABSTRACT FROM AUTHOR]

Participation in international industrial transfer (IIT) provides a significant opportunity and a motivation to improve China's industrial land production efficiency (ILPE). This study aims to investigate the overall role, heterogeneous impact and indirect mechanism of IIT in improving Chinese ILPE. This paper uses the Directional Distance Functions - Data Envelope Analysis (DDF-DEA) model to measure ILPE, economic output efficiency, and pollution reduction efficiency, the Global Malmquist Luenberger (GML) index to decompose the growth of ILPE into "technical efficiency change (EC)" and "technological change (TC)". The panel data of Chinese provinces from 2003 to 2018 and the Fixed-Effect model is used to examine the impact of IIT on ILPE. The primary outcomes suggest that participation in IIT has generally improved the ILPE in China. This promotion effect is evident after 2010, and IIT has a significant impact on the improvement of ILPE in extensive and inefficient areas. Similarly, IIT promotes the economic output efficiency of industrial land from the perspective of expected output and reduces unexpected output. This impact helps in improving pollution reduction efficiency of industrial land. The technology spillover brought by IIT improves the Chinese ILPE from two channels, including promoting technological progress and improving technical efficiency. However, the technology spillover mainly promotes the ILPE in land use high-efficient areas by promoting technological progress. Likewise, the ILPE is promoted by improving technical efficiency from a regional perspective in extensive and inefficient areas. This study provides valuable insights for the improvement of ILPE to optimize land resources. [ABSTRACT FROM AUTHOR]

Cheng H.; Wang B., 2019. Multiplier Effect of Science and Technology Innovation in Regional Economic Development: Based on Panel Data of Coastal Cities. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 883–890. Coconut Creek (Florida), ISSN 0749-0208. Science and technology innovation is the core power of economic development, but the influence mechanism effect of science and technology innovation and economic development is still a theoretical blind spot to be elucidated. The input of science and technology innovation factors leads to the multiplier effect of economic development through three levels of diffusion to realize high external economic benefits under low capital input. Through theoretical analysis and empirical research, this paper proves that: In terms of research samples of six coastal provinces and cities from 2000 to 2017, science and technology innovation factors have a strong multiplier effect on regional economic development; the input of new type of practical patent significantly improves the regional economic level in the current period and the lag phase effect is further improved; the input of R and D investment significantly improves the regional economic level in the current period, and the promotion effect is slightly decreased in the lag phase. At present, China's economic development is gradually moving towards marketzation. We should synchronously use "visible hands" to give policy incentives to regions with high capital stock for science and technology innovation and develop the multiplier effect of science and technology innovation in economic development through various paths. [ABSTRACT FROM AUTHOR]

Considering the enlarging inter-provincial disparities in China as regards carbon emissions and carbon intensity (carbon emissions per unit gross domestic product), this paper is the first study to investigate the inter-provincial carbon imbalance by constructing and employing the Kaya-Zenga index. We use China's panel data of provincial-level carbon emissions over 1995–2016 to quantitatively measure the levels of inter-provincial imbalance and polarization in carbon emissions and carbon intensity. Further, we decompose the Kaya-Zenga index into different contributing factors both regionally and structurally and perform a scenario analysis to identify the corresponding regionally differentiated countermeasures regarding carbon emission reduction. The results show that the imbalance in carbon emissions is mainly caused by imbalances in population scale and income level, while the imbalance in carbon intensity predominantly results from imbalances in energy efficiency and energy mix. In addition, for heavy manufacturing provinces, the respective emission-reduction strategy should aim at lowering energy intensity through local technology improvement and inter-regional technology transfer. For light manufacturing and high technology provinces, carbon emission reduction is harder to be achieved; however, a mix of policies of improving energy efficiency, optimizing energy mix, and industrial upgrading should be implemented. The results of the scenario analysis indicate that reducing imbalance in carbon intensity under different scenarios can lead to a substantial reduction in carbon emissions (up to 10%). • We investigate the inter-provincial carbon imbalance within China. • We construct the Kaya-Zenga index and decompose the index into four contributors. • We use a panel data set of 30 provincial-level regions in China over 1995–2016. • Carbon imbalance is mainly caused by imbalances in population and energy efficiency. • Reducing intra-group imbalance in carbon intensity can abate carbon emissions. [ABSTRACT FROM AUTHOR]

Economic growth and urbanization have been adequately studied due to their profound influence on pollution. However, the collective development of economy and urbanization poses a challenging problem in terms of reducing CO 2 emissions. One of the prerequisites for solving this problem is to examine the simultaneous impacts of economic growth and urbanization on CO 2 emissions. Within an extended STIRPAT framework, the present study aims to thoroughly investigate the combined nonlinear effects of economic growth and urbanization on CO 2 emissions using provincial panel data from China that spans the period of 1997–2016. Considering the heterogeneity and dynamicity across the panel, this is the first attempt to comprehensively explore the selected variables and the CO 2 emissions nexus by building a new two-way fixed-effects panel data partially linear additive model. The results show an inverted "U-shaped" nonlinear impact of economic growth on CO 2 emissions, but urbanization has a different influence, revealing a "roller coaster" pattern with three turning points. The results also suggest that the factor of energy consumption will lead to an increase in CO 2 emissions, while technology diffusion and industrial upgrading can facilitate the reduction of CO 2 emissions. To provide an in-depth understanding of these impacts, nonlinear marginal analyses are performed at different stages of socioeconomic advancement. In addition, the consistency of the empirical results and the merits of the suggested method are corroborated by the different estimation techniques. The conclusion recommends that the evaluation of carbon pollution needs to be heightened by further research from multidimensional perspectives, and the concepts of green production and low-carbon development should be promoted to achieve the sustainable goals of the whole society. • Explores the combined nonlinear effects of economic growth and urbanization on CO2 emissions. • Launches the methodology of panel data partially linear additive model estimation. • Shows an inverted "U-shaped" linkage between economic growth and CO2 emissions. • Reveals a "roller coaster" pattern between urbanization and CO2 emissions. [ABSTRACT FROM AUTHOR]