Regional Technological Innovation Research Articles

중국 지역별 과학기술 혁신역량 측정 및 공간적 차이 분석 -산둥성을 사례로-

최근 중국은 지역마다 과학기술 혁신역량 발전, 혁신형 도시 건설에 주력하 고 있다. 본 논문은 이러한 사회적 배경을 바탕으로 산둥성 여러 도시들의 기 술혁신 역량을 종합적으로 측정하였다. 선행연구를 바탕으로 도시의 기술혁신 역량 지표체계를 수립하고, 엔트로피 방법을 통해 산둥성 각 지역별 기술혁신 역량에 대한 종합적 측정을 진행하였다. 도시별 기술혁신역량의 종합점수에 의 거하여 체계적 군집화(클러스터링 기법)를 통해 산동성 17개 지급시를 고수준 기술혁신도시, 중간수준 기술혁신도시와 저수준 기술혁신도시 3가지로 분류하였 다. 각 유형별 도시의 기술혁신역량 현황을 종합하여 17개 지급시 기술혁신 유 형별 차이를 상세히 분석한 결과, 지난(济南), 칭다오(青岛)의 기술혁신역량이 크게 앞서가고, 옌타이(烟台), 웨이팡(潍坊), 웨이하이(威海)가 그 뒤를 이었다. 지닝(济宁)은 혁신도시 건설이 기대에 못 미쳤으며, 나머지 도시는 모두 혁신수 준이 낮게 나타났다. 실증결과 중국 지역별 기술혁신 수준 격차가 상당히 커 지역 견인효과가 불 균등함을 보여주었다. 이러한 기술혁신역량의 심각한 지역별 불균형은 중국 정 부가 대학교 및 과학연구기관, 금융서비스역량, 시장 변화 여건 등 분야에서 불균형 해소를 위한 정책적 노력이 필요함을 입증한다. 본 논문에서는 산둥성을 중심으로 지역별 과학기술 혁신역량에 대한 측정 평 가를 하였다. 이러한 시도는 다른 성ㆍ시 과학기술 혁신 역량 지수를 측정할 수 있다는 측면에서 기초 연구로 의의를 가지며 지역별 발전수준과 발전역량을 이해하는데 도움이 될 것으로 본다.

Does high-speed railway promote regional innovation growth or innovation convergence?

The paper utilizes an endogenous innovation growth model including high-speed railway (HSR) fares and speeds to explain how HSR affects regional technological innovation. Difference-in-Difference (DID) regression analysis shows that HSR has significantly promoted innovation growth and innovation convergence in China, with the effect value of 14.73% and 5.91% respectively. The conclusion that HSR promotes innovation growth is still valid through endogenous treatment of instrumental variable method. Various robustness analyses show that the more stations or lines connection, the more conducive to promoting innovation growth and innovation convergence. The conclusion is still robust after different time bandwidth is set. Further analysis shows that HSR has significantly promoted the innovation development and innovation convergence within and between the three regions of eastern China, central China and western China. The innovation spillover range of innovation center cities to non-innovation cities is 300 km. In addition, it is found that cities that have not opened HSR can also benefit from the connection of HSR in neighboring cities, thus promoting innovation growth, but the impact on innovation convergence is not as significant as the direct connection of HSR. The policy enlightenment of this paper is that in the face of innovation gap and regional innovation development inequality, in the planning and construction of HSR, it is suggested to coordinate the regional layout of investment in high-speed rail construction, which is not only conducive to promoting the innovation growth of these regions, but also conducive to narrowing the regional innovation development gap. In addition, remote and backward areas should seize the opportunity of opening high-speed railways to promote regional innovative growth, instead of making high-speed railways a channel for factors such as human capital to escape.

Regional technology gap and innovation efficiency trap in Chinese pharmaceutical manufacturing industry.

ObjectiveThere is a huge technology gap between regions in Chinese pharmaceutical manufacturing industry, which is the reality that must be faced. However, most of the available researches on innovation efficiency are based on the logic of a given technology level, ignoring the regional technological gap. This paper will stand from the perspective of technology gap and re-examine the innovation efficiency of pharmaceutical manufacturing industry in different regions of China and its impact on regional industrial competitiveness.MethodsWe use the DEA-BCC input-oriented model to measure innovation efficiency of 28 provinces from the data of China's pharmaceutical manufacturing industry. The threshold model is constructed, with technology level as the threshold variable, innovation efficiency as the main explanatory variable, and industrial competitiveness as the dependent variable. In the threshold model, 28 regions are divided into three technical groups, and further, the impact of innovation efficiency on industrial competitiveness in different groups is analyzed and compared.ResultsAccording to the empirical research results, an U-shaped efficiency trap has been found in Chinese pharmaceutical manufacturing industry, and the areas with medium technical level are at the bottom of the trap. The improvement of innovation efficiency does not necessarily promote the improvement of regional industrial competitiveness. Only in high-level and low-level technology groups, innovation efficiency has effectively promoted the improvement of industrial competitiveness. In addition, the intensity of R&D investment has a similar impact on industrial competitiveness.ConclusionsThe findings suggest that, regions in the efficiency trap should strive to seek opportunities for industrial transformation and focus on the industrial transformation of new technology, new industry and new opportunities, instead of blindly pursuing R&D investment intensity and superstitious innovation efficiency. So as to free up innovation resources for high-quality technological innovation in other regions. In addition, the Chinese government should make use of its public hospital system to normalize and expand the centralized drug procurement and eliminate the low-quality innovation.

Industrial College: A Study of New Models of Engineering and Technology Talent Training

The introduction of ‘Industrial College’ constitutes a supply-side structural reform in which higher education actively adapts to the industrial revolution and technological development to build academic subject clusters. This article explores the new organizational form of industrial colleges from the point of view of four aspects: history and origin, connotation and essence, form and model, and international experience. Second, it analyses the significance of cultivating practical engineering and technology talents in industrial colleges from application value and theoretical significance. Third, it suggests improving the organic circulation of four chains, including standard chain, institutional chain, goal chain, and information chain, and gradually forming the guarantee system of ‘setting standards – implementation process – monitoring results – feedback & evaluation’. Fourth, it expects to activate and strengthen the ability of universities to integrate regional industrial technology innovation and transformation, by reinforcing the exploration of the construction path for collaborative education and demonstrating the construction of the industrial college.

Does factor endowment allocation improve technological innovation performance? An empirical study on the Yangtze River Delta region.

Technological innovation is an important driving force for the regional economy's high-quality development, and determining ways to improve the condition and allocation efficiency of factor endowment is key to improving the performance of regional technological innovation. Considering the dynamic conditions of technological progress, we empirically study the endowment conditions and allocation efficiency of technological innovation factors input in the Yangtze River Delta region by using the translog production function to explore the interactive mechanism of innovation factors to technological innovation performance during 2000-2017. The results show the following: First, the three innovation factors-innovative human capital investment, research and development (R&D) fund investment, and fixed asset investment-contributed positively to technological innovation performance output in the Yangtze River Delta region, but there is an obvious gap between Anhui Province and the Jiangsu Province, Zhejiang Province, and Shanghai Municipality. Among the three factors, the contribution rate of R&D fund investment is relatively high, and technological innovation is dependent on R&D fund investment. Second, the biased technological progress of technological innovation factors in the Yangtze River Delta region shows a growth trend, and allocation efficiency of all three innovation factors improved continuously. The provinces' order from high to low allocation efficiency is Jiangsu Province, Shanghai Municipality, Zhejiang Province, and Anhui Province; Zhejiang Province showed the fastest improvement. Finally, the alternative elasticity coefficient of the three innovation factors in Jiangsu Province, Zhejiang Province, and Shanghai Municipality is greater than zero. The proportion structure of the input of technological innovation factors matches the regional technological progress. Technological innovation is in the effective economic range, but the fixed asset investment factors are relatively abundant, and there is room for improvement in the factor configuration structure. In Anhui Province, the alternative elasticity of innovative human capital investment and innovation R&D fund investment during 2000-2012 is less than zero, and the factor configuration structure keeps Anhui Province's technological innovation output in the uneconomic range, which is an internal factor that hinders the output of technological innovation performance in this province. They are not inconsistent that input and contribution rate of the innovation factors in the Yangtze River Delta region. The result of this study shows that technological innovation performance not only depends on the input of innovation factors, but also be affected by the allocation efficiency of innovation factors. In order to promote the economy's high-quality development in the Yangtze River Delta region, the government need not only pay attention to the input of innovation factors, but also pay more attention to improve the allocation efficiency of innovation factors.

Evaluation of Regional Science and Technology Innovation Policy Effect Based on Lasso and BP Neural Network

Evaluation of Regional Science and Technology Innovation Policy Effect Based on Lasso and BP Neural Network

Regional technological innovation and green economic efficiency based on DEA model and fuzzy evaluation

With the advent of green economy, it is of great significance to objectively calculate the green innovation efficiency of provincial industrial enterprises in China for achieving sustainable economic development. In this paper, the author analyzes the regional technological innovation and green eco nomic efficiency based on DEA model and fuzzy evaluation. Based on the latest development of traditional efficiency and productivity analysis theory, this study calculates the green innovation efficiency of 30 provincial industrial enterprises by using SBM model, while considering the relaxation of economic input-output problem. The results show that the SBM model improves the accuracy and authenticity of the economic efficiency evaluation of green innovation. The efficiency of green economy in most provinces is on the rise. At the same time, the intensity of R&D and industrial structure play a positive role in improving the efficiency of green economy. Through cluster analysis, the differences and causes of green economic efficiency of regional industrial enterprises are analyzed. In addition, the provinces should also consider the factors affecting the green economic efficiency of industrial enterprises, implement the innovation-driven development strategy in an all-round way, and promote the development of green economy.

The Flow Network of Chinese Scientists and Its Driving Mechanisms Based on the Spatial Development Path of CAS and CAE Academicians

Scientists are a core element of regional technological innovation and economic growth. Academicians of the Chinese Academy of Sciences (CAS) and Chinese Academy of Engineering (CAE) are outstanding representatives of Chinese scientists. The purpose of this paper is to reveal the characteristics of Chinese scientists’ space migration, depict the structural topology of their flow network and to analyze the driving mechanisms behind the characteristics of their space migration. We mainly used spatial statistics, complex network analysis, and a modified location quotient. Our main conclusions are as follows: (1) The spatial distribution of Chinese scientists at different development stages tends to converge. The Chinese scientists’ birthplaces are highly concentrated in the eastern coastal areas and the Yangtze River basin. Education locations are highly consistent, with clusters of global high-level educational resources at home and abroad, and their workplaces are mainly distributed in economically developed cities. (2) In terms of network characteristics, the spatial heterogeneity of the growth of Chinese scientists is obvious. Only a few cities, such as Beijing, Shanghai, and Nanjing, have higher degrees of node centrality, strength centrality, and betweenness centrality, so their networks’ hierarchical structures are pyramid-shaped and their core-periphery structures are prominent. By identifying the roles of the cities as network nodes, we found that only Beijing plays accomplished and stable roles, whereas other cities play a single role. (3) Regarding driving mechanisms, Chinese scientists’ spatial migration has been influenced by national policy, regional economic level, education level, and individual traits at national, regional, and personal scales. Therefore, the combined effects of various forces have driven the evolution of the flow network of Chinese scientists.

Analysis of the scientific and technological innovation efficiency and regional differences of the land–sea coordination in China's coastal areas

The overall strategy for land-sea coordination is important for scientific and technological innovation efficiency in China's coastal areas. In this paper, the country's mixed land and sea regions were selected for study, including two land and ocean subsystems with input and output index systems. Based on the variation coefficient method, the global Malmquist–Luenberger (GML) index was used to calculate the scientific and technological development efficiency of coordinated plans for China's coastal land and sea areas from 2006 to 2015 and to analyze the regional differences among these plans. The conclusions are as follows. First, the total factor productivity growth rate of science and technology innovation efficiency in China's coastal areas is primarily larger than 1 and at the frontier of efficiency. The efficiency of mixed areas is higher than that of separated land and sea areas, and the differences in regional technological innovation efficiencies has gradually narrowed. The change in technical efficiency is consistent with changes in the GML index, and the financial crisis of 2008–2009 had a significant positive impact on pure technical efficiency. Second, the coordinated plans for land and sea areas are realized and spatial differences in scientific and technological innovation efficiency in China's coastal areas are classified according to scientific and technological innovation in China's coastal areas. Hebei and Liaoning are classified according to the land efficiency type; Jiangsu and Zhejiang are classified as the marine efficiency-driven type; and the Shandong, Tianjin, Shanghai, and Pan-Pearl River Delta regions are classified as the efficiency of mixed land and sea areas type. Drivers of regional differences mainly include economic development levels, differences in industry structure, the personnel structure of scientific and technological systems, and the state of production and the influence of the government.

Innovation in Creative Industries: Does (Related) Variety Matter for the Creativity of Urban Music Scenes?

abstractThis article investigates the relation between different forms of (related) variety found in urban music scenes and innovation in music. While related variety has been found to be positively associated with several indicators of regional economic development and technological innovation, it remains unclear whether its merits also benefit innovation in creative industries. As innovation in creative industries is based on symbolic knowledge, the degree of variety in local contexts may affect the creativity of artists differently than the innovativeness of engineers and scientists. To test whether specialization, unrelated variety, or (semi)related variety is linked to innovation in creative industries, this contribution applies the concept of related variety to the context of urban music scenes. As innovation in creative industries is hidden from traditional innovation data, we utilize volunteered, geographic, and user-generated information from the social music platform last.fm. From relatedness measures between music genres, we generate our own classification system of music, which is used to calculate different related variety metrics of music scenes. Furthermore, our database allows for the identification of innovation in music as the emergence and combination of music genres. The results of this article suggest that semirelated variety promotes innovation in music, while related variety is only positively associated with combinatorial knowledge dynamics. Additionally, specialization limits innovation in music scenes. Hence, policy concerned with creative industries needs to analyze not only aggregate data but also the composition of regional symbolic knowledge bases.

DID model based research on the policy effect of national independent innovative demonstration zones

National Independent Innovation Demonstration Zone set up as combination of regional technology innovation policy in nine areas of Beijing Zhongguancun, East Lake in Wuhan, Shanghai Zhangjiang as a national independent innovation demonstration area as a sample of policy mix to when the impact of technological innovation ability by using Difference-In-Difference model. Studies have shown that compared to after the implementation of the policy, local regional technological innovation capability has increased, and fail to carry out the policy of Chongqing, Shenyang, Beijing and Wuhan, to carry out the policy of regional technological innovation capability enhancement is more obvious;The whole society investment in fixed, population density and area of technical level of regional technology innovation in inhibition, human capital, research funding, foreign real investment and government funding support to promote the regional technology innovation, After we re-estimate the same models by the stability test and conclude the similar results.

Financialization, Monetary Policy and Technological Innovation

Based on the research hotspot and the established status of the real economy financialization, this paper examines the impact of financialization on regional innovation from a macro perspective. In theory, economic financialization has an impact on regional innovation mainly through innovative “water reservoir effect” and “crowding effect”, and the overall impact depends on the net effect of the two. In view of this, based on the 2008-2016 provincial panel data, this paper analyzes the specific effects of regional financialization on technological innovation and analyzes the transmission path of effects based on the spread of financial regions. The study finds that, on the whole, financialization has a negative overall effect on regional innovation, and this conclusion is still stable after using the instrumental variable test. After considering the spatial factors, the financialization has a positive and spatial relationship between the regions, indicating that the financialization has a tendency to spread between regions; at the same time, the impact of financialization on regional technological innovation is still significantly negative. Considering the location heterogeneity, it is found that the negative effects of financialization are more significant in the central and eastern regions. After further examining the monetary policy, it is found that the relatively loose monetary policy actually strengthens the “crowding out effect” and further worsens the suppression of innovation by financialization. The research of this paper supplements the relevant research on the development and impact of China's financialization at the macro level, and provides important empirical evidence for the government's guiding funds to “deviate from reality”.

徐州市区域科技创新体系建设及综合评价研究——基于AHP和熵权法

徐州市区域科技创新体系建设及综合评价研究——基于AHP和熵权法

Research on the Construction of China's Science and Technology Innovation Service Platform Based on the Perspective of Collaborative Innovation

Collaborative innovation is a new form of national science and technology innovation. As a link and bridge for regional science and technology innovation, science and technology innovation service platform plays an important role in promoting the coordinated innovation of government, industry, universities and research institutions, and promoting the transformation and upgrading of regional industrial economic structure. This paper takes Jiangxi Province of China as an example. Through research and data statistics, it summarizes the construction achievements of Jiangxi Science and Technology Innovation Service Platform and analyzes the barriers that exist in the development process of the platform. At the same time, it summarizes and refines the successful experience of developed countries in the construction of Science and Technology Innovation Service Platform. On this basis, based on the collaborative innovation perspective of government, industry, universities and research institutions, the development path of Jiangxi science and technology innovation service platform is proposed from four aspects: Strengthening Policy Support and Perfecting Supporting Guarantee Mechanisms; Information resources co-construction and sharing and collaborative innovation; strengthening talent team construction and establishing scientific evaluation mechanism.

The Impact of MNCs’ R&D Centers Aggregation Level on Regional Innovation Capability

Based on the panel data of seven economically developed regions in China from 2006 to 2015, the STATA 15.0 is used to study the direct and indirect effects of the R&D center aggregation level on regional innovation capability by the fixed-effect regression method. The results show that, from its direct impact, active establishment of multinational companies R&D centers and their agglomeration would positively influence regional technological innovation ability. From the indirect effect, the aggregation of R&D center of MNCs improves regional innovation ability through the flow and agglomeration of talents, research and development funds. Finally, based on the research results, relevant suggestions are put forward.

Research on R&D Resource Allocation Efficiency Improvement Strategy in China

Focusing on short board is one of the key points to push forward the structural reform of the supply side and cross the "middle income trap". At present, China's economy into a new normal, economic growth from the original "factor-driven" into "innovation-driven." R&D as the core of scientific and technological innovation activities, its input scale and output efficiency has become a measure of a country or region of science and technology and innovation ability of the important indicators. In this paper, based on the research on the efficiency of R&D resources allocation and its influencing factors at home and abroad, this paper, based on the current development trend and actual situation of China's R&D, the lack of investment in R&D, the gap between regional industry and the lack of intellectual property protection, We will improve the efficiency of R&D resource allocation by improving the quality of personnel investment, promoting regional technological innovation, carrying out domestic and foreign cooperation and strengthening government cooperation.

The State of Innovation in Sweden and its Regions

The Northern Review 45 (2017): 57–75 https://doi.org/10.22584/nr45.2017.004This article focuses on the successful Swedish tradition in the field of innovation, but also discusses the flip side of an innovation culture that honours only radical innovation. Related to this tradition is a preference to measure innovativeness through patent data. Both these traditions imply a disadvantageous position for regions and companies located outside our large metropolitan areas. One problem relates to the interest in understanding how different degrees of innovativeness relate to different degrees of economic and social effects—a challenge that patent data, only to a very limited degree, addresses. This means that patent data disregards the fact that also incremental innovations “new to the region” or “new to the firm” might be powerful routes to a more dynamic development path, especially in more peripheral regions. To overcome such shortcomings, other measures and approaches are needed. One such approach developed and presented in this article is based upon Data Envelopment Analysis (DEA) and the Malmquist productivity index—employing Swedish longitudinal data, the article illustrates how they may be utilized to assess and make sense of regional technological innovation. Besides offering an unconventional picture of the regional innovation performance in Sweden, this methodological approach also identifies the northernmost part of Sweden (the Norrbotten region) as a region with its own path-breaking development trajectory. The article is concluded by discussing the region of Norrbotten as an example of a region that has traditionally capitalized on the exploitation and processing of natural resources and how such a region may diversify into new sectors using concepts such as related variety and smart specialization.

China’s regional science and technology innovation policy

Purpose Science and technology innovation policy has important strategic significance with respect to the promotion of an innovation orientation in our country, and the classification and measurement of regional science and technology innovation policy urgently require research attention. Design/methodology/approach In this paper, we use text mining and principal component analysis to analyze the classification and measurement of technology innovation policy based on data obtained from Zhongguancun Science Park. Findings The empirical results indicate that regional science and technology innovation policy can be divided into four types: authoritative, guiding, urgent and periodical. The key measurements are function type, intensity, resource supply, funding level and funding effectiveness. Originality/value A comparative analysis is performed to investigate the different types of regional science and technology innovation policy measurement. Additionally, the study’s limitations are discussed, and future research directions are proposed.

Exploring factors influencing the evolution of RTIE under resource constraints: an empirical study of the economic zone of Beibu Gulf of Guangxi in China

This paper explores the factors influencing on the evolution of Regional Technological Innovation Ecosystem (RTIE) under resource constraints in the less developed region. It takes the Economic Zone of Beibu Gulf of Guangxi in China, as an empirical sample and analyses the factorial path with the data of this region through establishing the structural equation model (SEM). The results show that the 'main factor of innovation ecosystem', 'the factor of resource constraints' and 'the environmental factor in innovation system' have positive influence on the healthy development of RTIE in this region. However, the factors of 'the environment of innovation policy' and 'the micro-market environment' have negative influence on the healthy development of the RTIE. This study provides some theoretical foundations and the suggestions for future research in evolution and policies of RTIE in the less developed region.

Simulation of complex regional technology innovation ecosystem under resource constraints

The development of a regional technological innovation ecosystem (RTIE) under resource constraints is uncertain and complex. Based on the complex systems theory, this paper discusses the evolution of RTIE through modelling and the simulation of a multi-agent system (MAS). Specifically, it proposes a theoretical model of RTIE under innovation resource constraints and explains the adaptive changes of the RTIE. It operationalises the concepts into dimensions of the quantified variables. Also, it uses the swarm software to simulate the evolution of the RTIE under innovation resource constraints. The simulation model incorporates an environment of innovation resource constraints and various situations under the control policies. The results show resource agents will gradually gather around enterprise agents. Enterprise and resource agents will be distributed differently in the regional space. The different control agent's actions may also lead to different evolution results. The study provides some theoretical foundations for future research in RTIE's evolution and regulation.