Spatial spillovers and value chain spillovers: evaluating regional R&D efficiency and its spillover effects in China

Research and development (R&D) efficiency assessment is an effective way for policymakers to develop strategies to increase the beneficial impacts of R&D. This study measures regional R&D efficiency from a multi-stage R&D perspective. It examines the spatial spillover effects and value chain spillover effects of R&D using panel data from 2009 to 2016 for 30 provinces in China. By estimating a spatial Durbin model, we find evidence of strong spatial dependence in R&D efficiency in China. With respect to R&D value chain effects, we find that R&D value chain spillovers took place intra-regionally but not inter-regionally. This finding indicates that in a knowledge flow context, there are two-way R&D value chain spillovers in which the forward spillover effects are stronger than the backward spillover effects. This finding adds important new knowledge to research on knowledge spillovers: distinguishing between value chain spillovers and spatial spillovers opens new avenues for future empirical inquiries.

     

Using patents and publications to assess R&D efficiency in the states of the USA

Even with the USA spending the largest amounts in R&D, its share in total patent grants worldwide has been declining. This decline is also evident in its share of world scientific publications. These developments have been termed by some as the “American Paradox”. Extant research on R&D efficiency and technological innovation capability has considered the USA as a homogeneous entity and has not focused at the sub-national level. This paper analyses the R&D efficiency of 50 US states and the District of Columbia. R&D efficiency is calculated as the ratio of patents granted and scientific publications to R&D expenditures. Only 14 states out of the 51 regions are found to exhibit positive changes in R&D efficiency between 2004 and 2008. Comparing this performance with that of the BRICS nations over the same period we find that Brazil, India, China and South Korea show significant improvements in R&D efficiency with India taking the lead. This research identifies the states in the US with the highest R&D efficiency and presents benchmarks which can be followed by policy interventions. The paper highlights the importance of conducting analyses of R&D efficiency using patents and publications at the sub-national level for informed policy making.     

A Business Intelligence Approach to Monitoring and Trend Analysis of National R&D Indicators

The economic growth and competitiveness of countries is strongly influenced by their national research and development (R&D) systems. Hence, national R&D managers must make appropriate decisions to develop their R&D systems. For this purpose, an integrated view on the dimensions of national R&D systems is much needed. Due to the distribution of relevant data sources for national, R&D indicators and the complexity of national R&D systems, establishing an integrated view is challenging. In this article, we propose a business intelligence architecture to monitor, analyze, and forecast national, R&D indicators. Data for these indicators are integrated from heterogeneous data sources. In a case study focusing on Iranian R&D indicators, a prototype system is designed and implemented to evaluate its effectiveness in practice. After monitoring the indicators using online analytical processing, trends for the indicators across 11 years are forecasted using time series analysis models. The prototype system provides an integrated view of the Iranian R&D system, so that national R&D managers can use the developed system for monitoring and trend analysis of Iranian R&D indicators. As a result of the analysis of these trends, implications and recommendations for the future of the Iranian R&D system are presented.     

Inter-country R&;D efficiency analysis: An application of data envelopment analysis

This study examines the relative efficiency of the R&D process across a group of 22 developed and developing countries using Data Envelopment Analysis (DEA). The R&D technical efficiency is examined using a model with patents granted to residents as an output and gross domestic expenditure on R&D and the number of researchers as inputs. Under CRS (Constant Returns to Scale), Japan, the Republic of Korea and China are found to be efficient, whereas under the VRS (Variable Returns to Scale) framework, Japan, the Republic of Korea, China, India, Slovenia and Hungary are found to be efficient. The emergence of some of the developing nations on the efficiency frontier indicates that these nations can also serve as benchmarks for their efficient use of R&D resources. The inefficiency in the R&D resource usage highlighted by this study indicates the underlying potential that can be tapped for the development and growth of nations.     

Effective R&D investment planning based on technology spillovers: the case of Korea

This study was performed to discuss an R&D investment planning method based on the technology spillover among R&D fields, from the point of view of technology convergence. The empirical analysis focused on a particular R&D group, such as university departments and specialized research institutes, since local technology combinations are more effective than distant combinations to create a new technology, according to previous research. In addition, worldwide technology competition is increasing, and with the recent convergence of various technologies and industries, strategies for R&D selection and resources allocation of particular R&D groups are becoming increasingly important. The empirical analysis uses a modified Decision Making Trial and Evaluation Laboratory method combined with information on patent citations to resolve the latent problems of the existing model, using as an empirical example the case of the Korea Institute of Geoscience and Mineral Resources (KIGAM), specialized in the geology and resources development R&D area. Through the empirical analysis, the KIGAM’s current R&D investment status is considered, and a reasonable R&D investment planning is suggested from the perspective of technology spillover. By using this framework, the magnitude of technology spillover from the R&D investment planning within a particular R&D group can be measured based on objective quantitative data, and the current R&D investment can be compared with recent global trends.     

Systemic aspects of R&D policy subsidies for R&D collaborations and their effects on private R&D

This paper analyses how context- and time-dependent factors determine the impact of R&D subsidies on firm behaviour with respect to private R&D expenditures. Based on German R&D survey data, we combine propensity score matching with a difference-in-difference estimator in order to measure the causal influence of public direct R&D project funding on firm behaviour. Our results indicate that (i) repeated participation in R&D projects on average leads to a higher increase in R&D expenditures than once-off funding; (ii) the aggregate effect of R&D funding on R&D expenditures of business firms is somewhat higher for business–business collaboration projects than for science–business collaboration projects; (iii) R&D expenditures of business firms that cooperate with science show a higher share of external R&D spending. Results of one particular cluster programme indicate that at least the short-term development of R&D does not so much depend on which programme direct R&D project funding is applied to.     

An empirical study of university–industry R&D collaboration in China: Implications for technology in society

This research investigates the growing phenomenon of university–industry (U–I) collaboration in high-tech strategic projects in China. After significant changes in the trading policies of 1978, China has gained heightened attention in technology and innovation. To achieve the stated strategic national goals, Research and Development (R&D) collaboration is essential. Organizations preferred to collaborate in order to share the burden of R&D costs and efforts. The academic outputs (research publications) of Chinese academic institutions and technology patenting ratio are increasing daily in China. These increasing numbers signal the importance of R&D. High-tech industries are inclined to share projects with universities. Foreign enterprises, state supported enterprises and local industry have played key roles to strengthening university–industry relationships.     

Vaccine R&D in Brazil: The effectiveness of push and pull regulations

Government regulations can guide the technological progress, investment in research and development (R&D), and institutional organization of a specific sector. In this context, using patent data, this study aimed to analyze the effectiveness of three laws that pertain to R&D in Brazilian pharmaceutical market for vaccines. The results reveal an increasing international interest in the Brazilian market since the promulgation of the Industrial Property Law. Despite its limitations, this study reveals significant efforts and promising results in Brazil with respect to ensuring that technological and industrial policies and strategies incorporate innovation in vaccine R&D and change the economy's competitive circumstances.     

Major factors affecting cross-city R&D collaborations in China: evidence from cross-sectional co-patent data between 224 cities

Scientific research activities cluster in cities or towns. Modern cities can play a crucial role in the national or regional innovation system. Strengthening R&D collaboration between cities can contribute to perfectly integrating various regional innovation systems. Using the cross-sectional co-patent data of the Chinese Patent Database as a proxy for R&D collaboration, this paper investigates the spatial patterns of R&D collaborations between 224 Chinese cities and the major factors that affect cross-city R&D collaborations in China. A spatial interaction model was used to examine how spatial, economic, technological and political factors affect cross-city R&D collaborations. The degree of centrality shows that cross-city collaborative R&D activities mainly occur in favored regions, advanced municipalities and coastal regions. The mean collaboration intensity for intra-provincial cross-city collaborations is 4.74; however, for inter-provincial collaborations, it is 0.69. The econometric findings reveal that spatial, economic, technological and political bias factors do yield significant influences on the frequency of cross-city R&D collaboration. Specifically, as evidenced by the model coefficient, it is more likely that R&D collaborations occur among cities that are connected by high-speed railways.     

Business Group Affiliation and R&D

This paper analyzes whether belonging to a business group enhances firms' propensity for and intensity of R&D based on the greater opportunities to finance and co-ordinate R&D strategies and internalize knowledge spillovers. Compared with the existing literature, this paper has the following novelties: (a) it examines how the organization and diversification of business groups influence the R&D investment of affiliated firms; (b) it analyzes the role of R&D spillovers among affiliated firms; and (c) it distinguishes between propensity for and intensity of R&D. We find that less diversified groups are more likely to centralize R&D, while in more diversified groups firms are more likely to be autonomous. We find that controlled companies are more likely to benefit from knowledge spillovers than firms at the head of the group. Finally, we find that R&D autonomy is significantly associated with both a higher propensity for and intensity of R&D in controlled companies.     

Scientific productivity paradox: The case of China's S&T system

Summary In 1985 China began the reform of its Science & Technology (S&T) sector inherited from the planned economy. To disclose the impact of the drawn-out reform on the efficiency of the whole sector, we measure the scientific productivity of China's S&T institutes. The analysis is based on R&D input and output data at the country aggregate and provincial level. We utilize Polynomial Distributed Lag model to uncover the structure of the lag between R&D input and output. The findings reveal that the growth rate of scientific productivity of China's S&T institutes has been negative since the 1990s.     

Industry evolution and key technologies in China based on patent analysis

Patents are the manifestation of the industry’s research and development (R&D) endeavor; therefore, this paper studies the industry evolution of and key technologies in China from the perspective of patent analysis. Patents in six types of industries, including Chemical (excluding Drugs), Computers and Communications, Drugs and Medical, Electrical and Electronics (E&E), Mechanical, and Others are analyzed in this study. Findings from the analysis show a steady increase of US granted utility patents in China as well as percentage of these patents in the world over the period between 2003 and 2008. All the above industries in China have been growing rapidly during this period, which is very different from the global industry development. Despite the rapid development, the citation rates of these patents have been low, reflecting a need for improvement in the quality of patents and R&D performance for these six industries in China in order to exert more influence in the industry world. The analysis on patents also reveals China’s industry distribution to be similar to the global industry distribution, with the exception of E&E industry which weights over one third of the total patents in technologies. The E&E industry is also the field with largest economic growth which rises more rapidly after 2006 with a sudden increase of patents in USPC 361. Detailed tracking of the key technology evolution reveals that 90% of the newly issued patents in USPC 361 after 2006 are owned by Foxconn Technology Co., Ltd, pointing to an unbalanced R&D environment in China’s E&E industry sector. By providing the insight into the evolution of China’s industrial and technological development through the perspective of patent analysis, this paper hopes to provide an objective statistic reference for future policy directions and academic researches.     

The Role of Time in Assessing the Economic Effects of R&D

This study investigates the impacts of R&D on firm performance. It extends previous research by constructing alternative stocks of R&D‐Capital that take into account that time plays an important role in assessing the pay‐off of industrial research. The results show that even when we employed R&D‐Capitals that placed more emphasis on the industrial research that had been undertaken 7 years ago, the effects of R&D were very (statistically) significant and relatively high, thereby suggesting that the life of R&D (on average) tends to be long. The results however, vary across organizations depending on both firm size and the technological opportunities that a company faces. It appears that the depreciation rate of R&D investments is higher in the case of technologically sophisticated firms. In contrast, strategic investments in industrial research generate a relatively constant effect on the performance of other firms, supporting the notion that the corresponding returns for such firms decay slowly.     

Energy R&D: investment challenge

Despite dependence on foreign oil that keeps countries like the US embroiled in the Middle East, and amid fears of global warming, research and development (R&D) funding for energy technologies has declined significantly during the last two decades throughout the industrial world. Investments in energy technology R&D, and in associated human and institutional capacity, are fundamental to our ability to respond to changing economic, energy, and environmental needs.Although there has been a recent wave of interest in R&D policy in general, and energy R&D in particular, this has not been translated into the needed increases in funding. In most OECD (Organization for Economic Co-operation and Development) member countries, government energy technology R&D budgets have been declining significantly in real terms since the early 1980s. The trends are particularly troubling given the pressing need to develop and utilize the clean energy and low carbon fossil-fuel energy technologies that will be critical in meeting our future energy needs, while addressing the local and global environmental problems we are facing.     

R&D and Productivity in High-Tech Manufacturing: A Comparison between Italy and Spain

Using data for 12 manufacturing industries over the period 1980–2006, we perform for Italy and Spain a dynamic panel estimation of the long-run elasticity of total factor productivity (TFP) with respect to R&D capital. In spite of recording a level of R&D capital lower than Italian industries, the technology-based industries in Spain have experienced a similar or higher long-run impact on TFP. This is mainly attributable to what occurred from the mid-1990s onwards when, thanks to increasing R&D efforts, the Spanish industries have been able to catch up with respect to the Italian ones. These findings suggest that, also in countries classified as technology followers, R&D investment is a crucial condition for boosting manufacturing productivity.     

R&;D market value under weak intellectual property rights protection: the case of India

The relationship between R&D and market value has attracted the interest of many scholars within different fields, but scant attention has been paid to the countries with weak protection of intellectual property rights (IPR). This is unfortunate, since this problem is potentially highly relevant for IPR policy in developing countries. In particular, several questions arise when the problem of R&D market value is analyzed in a country where IPR protection is weak. First, there are concerns regarding incentives (i.e., private returns) for firms to invest in R&D when IPR is only weakly protected. Second, significant differences could emerge in the market valuation of R&D investments of domestic and foreign firms, above all in those industries where spillovers are more likely. To examine these issues, this paper investigates the market valuation of R&D investments of a panel of 219 R&D-reporting domestic and foreign firms publicly traded in India with an empirical analysis. First, the market valuation of the R&D capital for the whole sample is positive and higher than those obtained in U.S. or European countries from similar analyses. Second, in the sub-samples of the domestic and foreign firms, the market value of R&D investments of foreign firms is not significantly different from zero, while the valuation coefficient of domestic firms is four times higher than that obtained on the whole sample. Third, in science-based industries the difference between domestic and foreign firms is smaller than in the other industries. The policy implications of these findings are discussed.     

The scientific wealth of European nations: Taking effectiveness into account

In this study we continue the application of Data Envelopment Analysis (DEA) to assess the efficiency and effectiveness of the R&D effort of European countries. We use GDP, active population and R&D expenditure as inputs, and publications and patents as outputs. Being effective means that, in order to obtain a maximum efficiency score countries are forced to perform on every output goal. A discussion of each country's performance and a comparison with May'sScience results concludes our analysis.     

Evaluation,ranking and selection of R&D projects by multiple experts: an evidential reasoning rule based approach

As a typical multi-criteria group decision making (MCGDM) problem, research and development (R&D) project selection involves multiple decision criteria which are formulated by different frames of discernment, and multiple experts who are associated with different weights and reliabilities. The evidential reasoning (ER) rule is a rational and rigorous approach to deal with such MCGDM problems and can generate comprehensive distributed evaluation outcomes for each R&D project. In this paper, an ER rule based model taking into consideration experts’ weights and reliabilities is proposed for R&D project selection. In the proposed approach, a utility based information transformation technique is applied to handle qualitative evaluation criteria with different evaluation grades, and both adaptive weights of criteria and utilities assigned to evaluation grades are introduced to the ER rule based model. A nonlinear optimisation model is developed for the training of weights and utilities. A case study with the National Science Foundation of China is conducted to demonstrate how the proposed method can be used to support R&D project selection. Validation data show that the evaluation results become more reliable and consistent with reality by using the trained weights and utilities from historical data.     

Will China’s quest for indigenous innovation succeed? Some lessons from nanotechnology

Over the past decade, the Chinese state has made major efforts to transition China’s economy away from a focus on manufacturing, and towards a focus on generating indigenous innovation in R&D intensive fields such as nanotechnology. This goal has been pursued through a comprehensive industrial policy framework that aims to give preferential treatment to Chinese companies in domestic markets while also devoting significant resources towards basic and applied R&D, building science parks and research centers, funding focused venture capital funds, and recruiting prominent expatriate scientists and entrepreneurs from universities and businesses abroad. This paper, based on interviews with scientists, engineers, entrepreneurs, and venture capitalists in Shanghai, Suzhou, and Beijing, examines the strengths and weaknesses of China’s push for indigenous innovation. We use the case of nanotechnology to address the pressing question of why China continues to underperform with regards to generating innovative, high-tech companies and products, despite heavy public R&D investment and the presence of one of the world’s largest talent pools of potential scientists, engineers and entrepreneurs.     

R&D policy instruments – a critical review of what we do and don’t know

In recent years, the term “policy instrument” has been used frequently with regard to R&D policy and innovation policy. This article examines the development of the term as part of a body of research known as “policy design”. Over the last 50 years, there has been substantial progress in setting policy design on a more systematic basis, with the development of established concepts and analytical frameworks, including various taxonomies of policy instruments. However, with just a few exceptions, this body of research seems to have had little impact in the world of R&D policy. The paper reviews the literature on R&D policy instruments, identifies a number of challenges for R&D policy instruments in the light of four transitions and sets out a research agenda for the study of R&D policy instruments, before ending with a number of conclusions.