Observing regional divergence of Chinese nanotechnology centers

Motoyama, Yasuyuki; Cao, Cong; Appelbaum, Richard P.

doi:10.1016/j.techfore.2013.02.013

Cited by 16 publications

(8 citation statements)

References 51 publications

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“…Results show that public nano-funding has been significantly contributing to improving nanotechnological output. Although it is uncertain whether financial support from government can compensate for the absence of private capital and viable markets, these results fit with the general view that Chinese policies on nanotechnology development follow a top-down approach (Motoyama et al, 2014).…”

Section: Effect Of Fundingsupporting

confidence: 52%

“…Nevertheless, we observe that lagging regions are catching up rapidly in nanotechnology output. While this raises the potential role played by spillovers from leading regions to lagging regions in China, a recent study on the growth of nanotechnology in China points to very little proximity-driven spillovers of nanotechnological knowledge (Motoyama, Cao, & Appelbaum, 2014). This is, of course, not a surprising result given the vast distances separating China's peripheral regions from its leading regions along the East coast.…”

Section: Research Context: Nanotechnology Development In Chinamentioning

confidence: 98%

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Exploring the spatial dimensions of nanotechnology development in China: the effects of funding and spillovers

Wang

Jacob

2018

Regional Studies

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This paper investigates the factors driving nanotechnology development in Chinese regions. Advanced regions of China have spearheaded the country's rapid growth in nanotechnology, aided by substantial support from the government. While this head start could potentially perpetuate regional inequalities through agglomeration economies, the results suggest that knowledge spillovers exert a substantially greater impact in peripheral regions compared with the advanced ones, and may thus be compensating for the limited institutional support they receive and their weak technological capabilities. This research contributes to the regional innovation literature by highlighting that a formal scientific network can counteract the forces of agglomeration economies and spur innovation in peripheral regions.

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Section: Effect Of Fundingsupporting

confidence: 52%

Section: Research Context: Nanotechnology Development In Chinamentioning

confidence: 98%

Exploring the spatial dimensions of nanotechnology development in China: the effects of funding and spillovers

Wang

Jacob

2018

Regional Studies

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“…In January 2006, China held the first National Conference on Science and Technology in the new century, releasing "Guidelines for the National Medium-and Long-Term Science and Technology Development Program (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019)(2020)" toward building China into an "innovation-oriented country" by 2020. However, the rise in regional inequality in China during the reform era has been widely documented, and this inequality also applies to innovative activities (Li and Wei 2010;Liao and Wei 2012;Motoyama, Cao, and Appelbaum 2014;Wei and Ye 2009). It has been reported that innovative activities are overwhelmingly concentrated in more advanced economic regions such as Beijing and Shanghai (Liefner, Wei, and Zeng 2013;Motoyama, Cao, and Appelbaum 2014).…”

Section: Introductionmentioning

confidence: 99%

Analyzing the Space–Time Dynamics of Innovation in China: ESDA and Spatial Panel Approaches

Wang¹,

Cheng²,

Ye³

et al. 2015

Growth and Change

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Through applying exploratory spatial data analysis (ESDA) and confirmatory spatial data analysis (CSDA), this paper examines the space–time dynamics of innovation at the provincial level in China from 2000 to 2011. We first investigate the trend of regional inequality in innovation in China and then use ESDA methods to visualize the space–time relationship between patent applications and innovation determinants. Impacts of innovation determinants on the space–time dynamics of innovation are also examined by analyzing the knowledge production function with the spatial panel Durbin model. Knowledge spillovers from both the R&D and the innovation outcome perspectives are highlighted in CSDA. We have found an increasingly intensified coastal–interior divide with growing spatial clusters and more innovative activities in the coastal region. We have also found a close space–time relationship between innovation and its determinants. Lastly, innovation spillovers cross province boundaries, and knowledge from a province's neighboring provinces has substantial effects on innovation activities of the province. This paper highlights positive knowledge spillover effects between regions, the close relationship between innovation and its determinants, and the importance of spatial externalities in innovation activities.

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“…As to China's economy, it develops on the base of non-innovative and even outdated technologies. On the other hand, in recent years China has achieved a rather significant progress in this field (e.g., Kim et al, 2009;Ma et al, 2009;Hu and Phillips, 2011;Zhang and Gao, 2011;Lai et al, 2012;Chen et al, 2012;Xiang et al, 2013;Motoyama et al, 2014;Fuller, 2014 TFS***). Today China ranks third in the world in terms of the number of patents; in addition, China's output of research articles has expanded in a very significant way (Kostoff et al, 2007a,b,c;Kostoff, 2012); a very high number of patent grants attested in the recent years in China is very important; yet, a rather pronounced accelerating dynamics is of no less importance (see, e.g., Liu and Sun, 2009;Tseng, 2009;The World Bank…, 2012: 177;Boeing and Sandner, 2011: 17;WIPO, 2014; see also Fig.…”

Section: Why Is the Growth Model Difficult To Change?mentioning

confidence: 99%