State Information Center

Beijing, China

State Information Center

Beijing, China
Time filter
Source Type

Chen W.,Wuhan University | Jiao H.,Wuhan University | Zeng Q.,Shanghai University of Finance and Economics | Wu J.,State Information Center
Pacific Asia Conference on Information Systems, PACIS 2016 - Proceedings | Year: 2016

Understanding the formation of supply chain flexibility is important. We draw on the organizational learning perspective to examine how inter-organizational systems (IOS) enabled collaborative knowledge creation can enhance the supply chain flexibility. Empirical results from 141 supply chain enterprises support most of our hypotheses. The results show that, (1) IOS use for exploration has positive effects on supply chain flexibility and collaborative knowledge creation plays a partially mediated role between them; (2) Market uncertainty moderates the relationship between IOS use for exploration for collaborative knowledge creation. And (3) under the greater uncertainty in the market environment, the relationship between company's collaborative knowledge creation and supply chain flexibility becomes stronger. This result suggests when supply chain enterprises face market uncertainty, they need to improve the level of IOS use for exploration to facilitate understanding of the market, which will improve the supply chain flexibility.

Qiu S.,Tsinghua University | Liu X.,University of Chinese Academy of Sciences | Gao T.,State Information Center
Research Policy | Year: 2017

This study compares the university spillover effect of two types of knowledge, localized knowledge from domestic collaboration and distant knowledge from international collaboration, and investigates their spillover effect on local firms’ innovation. The findings of this study challenge the conventional idea that international collaboration, especially collaboration with developed countries that possess frontier knowledge, better promotes innovation in developing countries. For the period from 1999 to 2004, only in first-tier regions of China do domestic and international university collaborations show a positive relation with local corporate innovation. In the period from 2005 to 2012, the positive spillover effect of both types of collaboration spreads to second-tier regions. However, international collaboration is negatively associated with firms’ innovation in the least developed regions. Furthermore, domestic collaboration has shown a larger positive impact on corporate innovation than international collaboration in recent years. In our paper, the regional absorptive capacity was identified to explain this puzzle. We argue that the universities of relatively developed regions should build research collaborations with both local and global universities to promote local innovation. Conversely, for underdeveloped regions, universities should emphasize local technological demand rather than blindly pursue international collaboration. © 2017 Elsevier B.V.

Wen Z.,Beijing Normal University | Wen Z.,University of Pittsburgh | Wen Z.,State Information Center | Liang X.,University of Pittsburgh | And 2 more authors.
Water Resources Research | Year: 2012

A new multiscale routing framework is developed and coupled with the Hydrologically based Three-layer Variable Infiltration Capacity (VIC-3L) land surface model (LSM). This new routing framework has a characteristic of reducing impacts of different scales (both in space and time) on the routing results. The new routing framework has been applied to three different river basins with six different spatial resolutions and two different temporal resolutions. Their results have also been compared to the D8-based (eight direction based) routing scheme, whose flow network is generated from the widely used eight direction (D8) method, to evaluate the new framework's capability of reducing the impacts of spatial and temporal resolutions on the routing results. Results from the new routing framework show that they are significantly less affected by the spatial resolutions than those from the D8-based routing scheme. Comparing the results at the basins' outlets to those obtained from the instantaneous unit hydrograph (IUH) method which has, in principle, the least spatial resolution impacts on the routing results, the new routing framework provides results similar to those by the IUH method. However, the new routing framework has an advantage over the IUH method of providing routing information within the interior locations of a basin and along the river channels, while the IUH method cannot. The new routing framework also reduces impacts of different temporal resolutions on the routing results. The problem of spiky hydrographs caused by a typical routing method, due to the impacts of different temporal resolutions, can be significantly reduced. © 2012. American Geophysical Union. All Rights Reserved.

Liu Y.,CAS Institute of Policy and Management | Xiao H.,State Information Center | Zikhali P.,The World Bank | Lv Y.,China Agricultural University
Sustainability (Switzerland) | Year: 2014

An extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model, incorporating factors that drive carbon emissions, is built from the regional perspective. A spatial Durbin model is applied to investigate the factors, including population, urbanization level, economic development, energy intensity, industrial structure, energy consumption structure, energy price, and openness, that impact both the scale and intensity of carbon emissions. After performing the model, we find that the revealed negative and significant impact of spatial-lagged variables suggests that the carbon emissions among regions are highly correlated. Therefore, the empirical results suggest that the provinces are doing an exemplary job of lowering carbon emissions. The driving factors, with the exception of energy prices, significantly impact carbon emissions both directly and indirectly. We, thus, argue that spatial correlation, endogeneity and externality should be taken into account in formulating polices that seek to reduce carbon emissions in China. Carbon emissions will not be met by controlling economic development, but by energy consumption and low-carbon path. © 2014 by the authors.

Liu Y.,CAS Institute of Policy and Management | Xiao H.,State Information Center | Lv Y.,China Agricultural University | Zhang N.,Jinan University
Journal of Cleaner Production | Year: 2015

China's urbanization is rapidly proceeding while bringing marked impact on the energy consumption. This paper contributes to current literature by using an improved spatial econometric model Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) to investigate the effect of urbanization on energy consumption for China's regions. The impact of urbanization is further disaggregated into direct and indirect impacts from the perspective of spatial econometrics. Results show that, if the urbanization level increases by 1.0%, energy consumption levels will correspondingly decrease by 0.089%. The spatial spillover effect on adjacent areas is positive: a 1.0% increase in one specific area's urbanization level leads to a 0.136% increase in an adjacent area's energy consumption. It is suggested that, it is essential to devote major efforts to energy conservation, in the process of improving the new-type urbanization. In particular, disaggregating China's targets for controlling energy consumption into smaller targets for different regions will contribute to controlling the growth of energy consumption. © 2015 Elsevier Ltd.

Lin C.,Tsinghua University | Dong Y.,Tsinghua University | Shan Z.,State Information Center
Jisuanji Yanjiu yu Fazhan/Computer Research and Development | Year: 2014

The increasing demand on space communication stimulates the internetworking and space-ground integration for space communication systems. Space networks are featured in heterogonous subnets, dynamic topology, large transmission delay, and high link errors. TCP/IP protocol suite requires stable connectivity and short transmission delay, which cannot be satisfied in space networks. As a result, existing protocols for the current Internet cannot be directly applied to space networks. Delay/disruption tolerant network (DTN) is a general message-oriented overlay network architecture that can be adapted to space networks. This makes DTN a very promising approach for interconnecting space communication systems. This paper first demonstrates the system architecture which applies DTN in space internetworking service (SIS), and then analyzes the key components and working patterns including protocol stack, message forwarding mechanism, naming and addressing, licklider transmission protocol (LTP), etc. Then we give a real scenario of Mars exploration. By surveying some key technologies and research trends, we analyze some technical problems to be solved and propose some future research directions including routing, security, and QoS control. And then, we introduce related development efforts, practice, and aircraft verification projects. Finally, we analyze the prospects for the research and application of DTN and SIS technologies in China.

News Article | April 25, 2016

They are also set to benefit from a new policy that liberalizes the transfer of technology from universities and institutes to companies and shifts from basic research to practical applications. The new technology transfer policy could have a greater impact on chemistry in China than the expected funding increase, observers say. The changes come after the conclusion in March of China’s annual parliament, the National People’s Congress (NPC), in Beijing. This is a transitional year for China as it moves from the 12th to the 13th five-year plan, which covers 2016–20. In these five-year plans, the Chinese government maps out how it will develop the country socially and economically, an approach China adopted from the Soviet Union in the 1950s. The newest plan includes a push for major breakthroughs in basic research, applied research, big data, and what the government calls “exploring frontiers,” which involves disciplines such as marine science. Speaking at NPC, Wang Yuanhong, senior economist from the State Information Center, explained how the government is increasing the ratio of deficit to gross domestic product to provide an additional $72 billion to spend on pro-growth measures. This includes setting up national-level efforts to boost research and innovation as China looks to science to fuel its slowing economy. The government estimates that scientific research will account for 60% of economic growth by 2020. During a news conference at NPC, Minister for Science & Technology Wan Gang confirmed that China will continue to increase research funding. Spending on R&D has increased by an annual average of 11.4% from 2012 to 2015 and will reach 2.5% of gross domestic product by 2020, up from 2.1% in 2015. Wan said overall R&D expenditure in China in 2015 amounted to $215 billion, 77% of which came from companies. Of that figure, $10.3 billion went to basic science, according to a summary from China’s National Bureau of Statistics that was released in advance of the full figures, which have not yet been made public. Yu Biao, vice director of Shanghai Institute of Organic Chemistry and director of State Key Laboratory of Bioorganic & Natural Products Chemistry, tells C&EN that work to address issues of health, energy, and climate change are important and reflect the Chinese government’s support of applied chemistry research. But he predicts that “it will be difficult to secure support for pure chemistry [research] and publishing papers.” Jay Siegel, dean of Tianjin University’s School of Pharmaceutical Science & Technology, agrees. “China is not a country that at this moment places a heavy importance on very basic research,” he says. “It wants to move toward basic science, but it’s a country that sees technology as a way to drive its economy in the next five years.” Yu foresees a strengthening of the relationship between basic and applied research in China. “The inherent mode of research is going to undergo a transformation,” he says. “Interdisciplinary and practical research will receive encouragement and vigorous support.” Chemists will need to consider focusing on problems in these areas of science. China’s government wants to make research outcomes more easily available to small businesses as well as big enterprises as part of its “Made in China 2025” policies aimed at boosting the economy. National research institutes and universities will be able to sell their intellectual property to businesses without needing national-level approval, which has previously involved lengthy waits. All profits earned on the sales will now be kept by the institutes where the research was conducted. New incentives aimed at researchers themselves may further speed up the commercialization of scientific research in China. At least 50% of the proceeds from the sale of findings will go to the researchers themselves. They will be able to work for the companies that buy their research for up to three years while maintaining their positions at the institute where they did the research. It is hoped that this will encourage greater productivity. Gao Xudong, deputy director of the Research Center for Technological Innovation at Tsinghua University, told People’s Daily, the official newspaper of the Chinese Communist Party, that this change should also resolve a fundamental issue: “Some enterprises who bought scientific research findings could not fully use them due to a lack of understanding of the findings.” In light of the increasing push to transfer technology to industry, Tianjin University in 2013 opened China’s first national center for patent and intellectual property. The Tianjin University Technology Transfer Center now has 18 full-time patent brokers who work on moving technology from the university to industry. “Passing greater autonomy to universities and cutting the red tape on the reporting for grants involving science and technology is a very big thing because, in general, funds have been very controlled. So if we see policies that allow for more entrepreneurial ventures within the university—your degree programs, new directions for research—that the university can control, then we get bottom-up control. This will have a big impact on research in general, and chemistry is poised to benefit enormously,” Siegel says.

Liu Y.,CAS Institute of Policy and Management | Xiao H.,State Information Center | Zhang N.,Jinan University
Sustainability (Switzerland) | Year: 2016

This paper proposes an extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model to investigate the factors driving industrial carbon emissions in China. In the first stage, a spatial Durbin model is applied to investigate the determinants of regional industrial carbon emissions. In the second stage, a geographically and temporally weighted regression is applied to investigate temporal and spatial variations in the impacts of these driving factors on the scale and intensity of regional industrial carbon emissions. The empirical results suggest that the provinces with low carbon emissions act as exemplars for those with high carbon emissions and that driving factors impact carbon emission both directly and indirectly. All of the factors were investigated, except energy intensity, energy price, and openness, significantly impact carbon emissions. Overall, the results suggest that spatial correlation, heterogeneity, and spillover effects should be taken into account when formulating policies aiming at reducing industrial carbon emissions. The paper concludes with relevant policy recommendations taking full account of the regional industrial carbon emissions, heterogeneity and spillover. © 2016 by the authors.

Wu S.,University of Science and Technology Beijing | Feng X.-D.,University of Science and Technology Beijing | Shan Z.-G.,State Information Center
Jisuanji Xuebao/Chinese Journal of Computers | Year: 2012

Missing data processing is an important problem of data pre-processing in data mining field. Traditional missing data filling methods are mostly based on some statistical hypothesis, such as probability distribution, which might not be the most applicable approaches for data mining of large data set. Inspired by ROUSTIDA, an incomplete data analysis approach not using probability statistical methods, MIBOI is proposed for missing data imputation based on incomplete data clustering. Constraint Tolerance Set Dissimilarity is defined for incomplete data set of categorical variables, so the general dissimilarity of all the incomplete data objects in a set can be directly computed, and the missing data is imputed according to the incomplete data clustering results. The empirical tests using UCI benchmark data sets show that MIBOI is effective and feasible.

Wang G.,Guangxi University | Wang G.,Central South University | Shan Z.,State Information Center
Information Processing Letters | Year: 2012

Mesh networks have been applied to build large scale multicomputer systems and Network-on-Chips (NoCs). Mesh networks perform poorly in tolerating faults in the view of worst-case analysis, so it is practically important for multicomputer systems and NoCs manufactures to determine the lower bound for the mesh network connectivity probability when the node failure probability and the network size are given. In this paper, we study the topic based on k-submesh model under two fault models: Each node has uniform or nonuniform failure probability. We develop a novel technique to formally derive lower bound on the connectivity probability for mesh networks. Our study shows that mesh networks of practical size can tolerate a large number of faulty nodes and maintain higher connectivity probability, thus are reliable and trustworthy enough for multicomputer systems and NoCs. For example, suppose we are building a mesh network of 40 000 nodes (e.g., M200 ×200) and require a network connectivity probability 99%, we only need to bound the uniform node failure probability by 0.25%. On the other hand, for the same size network M200 ×200, the mesh network connectivity probability can maintain 95.88% even the network runs one million seconds uninterruptedly under exponential distribution node failure probability with failure rate 10 -9 level. © 2012 Elsevier B.V. © 2012 Elsevier B.V. All rights reserved.

Loading State Information Center collaborators
Loading State Information Center collaborators