Regional Collaborative Innovation Research Articles

Dual circulation strategy, regional healthcare development, and medical collaborative innovation efficiency: evidence from Chinese cities.

This study analyzes panel data of Chinese cities from 2003 to 2018 as a sample in the context of the dual circulation strategy in China to ascertain the impact of urban healthcare development on medical collaborative innovation efficiency by using the GS2SLS method. Furthermore, it empirically examines the influence mechanism of regional healthcare development on medical collaborative innovation efficiency by using a threshold regression model. Additionally, we identified the heterogeneity of this impact in different cities. The results show the following: (1) There is a significant positive spatial correlation between regional healthcare development and medical collaborative innovation efficiency; (2) Under the dual circulation strategy, the regional investment level in international circulation has the most significant role in the overall strategy, and domestic circulation has been significantly improved after the launch of the innovation-driven strategy; (3) The results of the threshold test show that while domestic and international circulation promote the efficiency of collaborative innovation by 0.83, the promotion effect is more obvious under a higher regional healthcare development level. The research in this paper can provide specific guidance for the development of China's healthcare industry under the background of dual-cycle strategy, and can also provide valuable reference for developing countries in the world.

How does digital infrastructure affect industrial eco-efficiency? Considering the threshold effect of regional collaborative innovation

The implementation of Digital China and Made in China 2025 strategies has brought guiding the rapid development of digital infrastructure (DI) and industrial ecology into focus. Based on Beijing–Tianjin–Hebei (BTH) city data from 2011 to 2020, this study empirically investigates the influence mechanism and spatial effect of DI and regional collaborative innovation (RCI) on industrial eco-efficiency (IEE) using the improved gravity model and super-efficiency slacks-based measure model. The relevant findings are as follows: (1) Static and dynamic analyses show that DI significantly improves IEE. (2) The moderating effect test shows that RCI strengthens the effect of DI on IEE. (3) The threshold effect test captures a U-shaped nonlinear relationship between DI and IEE at different RCI intervals. In the positive stage, the improvement effect of DI on IEE presents marginal increasing characteristics. (4) For the spatial perspective test, the BTH city's DI and IEE exhibit a positive spatial correlation, and gradually form H–H and L–L cluster states. Furthermore, the city's DI improves the local city's IEE and benefits neighboring city's IEE, revealing spatial spillover effect. This study has valuable reference significance for other regions to simultaneously solve industrial development and environmental problems by advancing DI.

Research on the Impact of Enterprise Innovation and Government Organization Innovation on Regional Collaborative Innovation

Improving the regional innovation system and developing new organizational innovations to continuously enhance regional innovation capabilities are key measures for building a regional innovation hub and achieving high-quality economic development. This study first theoretically elucidates the impact mechanism of enterprise innovation agglomeration and government policy uncertainty on regional innovation capability, and thus clarifies such impact on regional organizational innovation. Based on urban panel data, this article empirically analyzes their impact on regional innovation. Based on the research results, the agglomeration of manufacturing industry in cities can significantly improve regional innovation capabilities. The policy uncertainty brought about by the mobility of municipal party secretaries has a restraining effect on the enhancement of regional innovation capabilities. The higher the degree of marketization in a city, the more significant the role of manufacturing agglomeration in enhancing regional innovation capabilities, thereby weakening the inhibitory effect of policies.

The impact of industrial digital transformation on green development efficiency considering the threshold effect of regional collaborative innovation: Evidence from the Beijing-Tianjin-Hebei urban agglomeration in China

Promoting industrial digitalization and deepening regional collaborative innovation is essential for achieving urban green and sustainable development. This paper constructs a differential game model based on theoretical analysis and reveals the influence mechanism of industrial digitalization and regional collaborative innovation on urban green development efficiency (GDE). After that, this paper uses the entropy method, Super-SBM model, and improved gravity model to measure the level of industrial digitalization, urban GDE, and regional collaborative innovation, respectively. Then, this paper constructs the fixed-effects model, SDM model, moderating-effects model, and threshold model, then uses the panel data of the Beijing-Tianjin-Hebei (BTH) urban agglomeration during 2011–2020 for empirical testing. The results show that: (1) industrial digitalization significantly improves urban GDE. (2) Overall, 2011–2015 is the rapid development period of BTH industry digitalization, and 2015–2020 is its stable development period. However, there are apparent spatial differences and imbalances. (3) Industrial digitalization has a significant spatial spillover effect that can enhance local and surrounding cities' GDE. (4) Regional collaborative innovation can directly enhance urban GDE, and has a positive moderating effect on industrial digitalization to enhance urban GDE. (5) The regional collaborative innovation has two thresholds of 3.9851 and 6.6184. With the collaborative innovation level improving, the main effect intensity steadily increases.

Technological Catch-Up, Innovation, and Productivity Analysis of National Innovation Systems in Developing Countries in Africa 2010–2018

This study investigates the levels and determinants of regional innovation catch-up, frontier shift, and productivity growth of African national innovation systems from 2010 to 2018. The study relied on the World Development Indicators data for 28 African countries. Non-radial non-oriented Data Envelopment Analysis (DEA) and bootstrapped truncated regression were the central estimation methodologies. The results revealed that 18% of Africa’s national innovation systems had experienced progress in the catch-up and frontier shift indexes. Further results showed that 21% had experienced total factor productivity growth. Nigeria and South Africa were on the region’s efficient frontier and had achieved the most technological advancement. In addition, Ghana and Senegal had the most productive national innovation systems. The results suggested that national innovation systems in Africa had experienced marginal progress. Further results indicate that the population growth rate and GDP per capita are the critical determinants of African national innovation systems, efficiency, technical efficiency, and productivity performance. Consequently, the implications of the results to policy are twofold. First, African countries should use benchmarking practices with the region’s best-performing national innovation systems. Lastly, African countries have the potential to grow their economies through regional collaborative Science, Technology, and Innovation practices.

The impact of environmental regulations on the performance of regional collaborative innovation-in case of China's 30 provinces.

With rapid economic growth in the twenty-first century, innovation has become an essential component of national development, and industry-university-research regional collaborative innovation is the key to implementing China's innovation plan. Using panel data from 30 provinces and cities in China (excluding Tibet Autonomous Region) from 2011 to 2018, this paper employs the two-stage dynamic DEA model to develop a rating index system of regional collaborative innovation performance, which is divided into knowledge innovation stage and technology innovation stage, and measures the collaborative innovation efficiency of 30 provinces in China. The environmental regulation score is then determined by using the entropy method. Finally, an experimental application of the panel Tobit model is conducted to investigate the impact mechanism of environmental regulation on regional collaborative innovation. The results reveal that the collaborative innovation efficiency values of the majority of provinces are between 0.5 and 0.7, leaving ample room for growth. When the efficiency value of collaborative innovation is broken down by region, the eastern, central, and western regions show a pattern of "rising in the east, stable in the center, and falling in the west." The findings of the Tobit regression reveal that the effect of environmental regulation on regional collaborative innovation performance follows a "U"-shaped distribution, confirming the "Porter Hypothesis." This study proposes remedies and proposals to enhance regional collaborative innovation performance from the perspective of environmental regulation.

The Impact of Science and Technology Finance on Regional Collaborative Innovation: The Threshold Effect of Absorptive Capacity

The collaborative innovation of Beijing-Tianjin-Hebei region is faced with prominent problems such as the large gap in innovation resources and capability. In addition, science and technology (S&T) finance provides the approach to promote the flow of regional capital, technology and talents, which can facilitate the coordinated development of Beijing-Tianjin-Hebei region. Therefore, this study takes the Beijing-Tianjin-Hebei region as an example to explore the mechanism of different S&T finance on regional S&T collaborative innovation. Based on the provincial panel data of Beijing-Tianjin-Hebei region from 2009 to 2020, this paper constructs a dynamic panel threshold model with different regional absorptive capacities (technology level and economic base) as threshold variables to analyze the impact of public and market S&T finance on regional collaborative innovation. The main findings of this paper are as follows: first, the overall level of regional collaborative innovation in Beijing, Tianjin and Hebei is low, and public and market S&T finance significantly affects regional collaborative innovation in Beijing, Tianjin and Hebei. Specifically, public S&T finance plays an inhibitory role on regional collaborative innovation, and market S&T finance positively affects regional collaborative innovation. Secondly, both types of S&T finance have obvious heterogeneous threshold characteristics of absorptive capacity on regional collaborative innovation. Once the absorptive capacity of both regions breaks through the critical scale, the inhibiting effect of public S&T finance on regional collaborative innovation shows a weakening trend; with the improvement of technology level, the positive influence of market S&T finance on regional collaborative innovation keeps increasing. With the improvement of economic base, it shows a shift from negative to positive. The research findings provide theoretical and practical guidance for accelerating the pace of S&T innovation and the implementation mechanism of regional coordinated development.

Growth Trends and Heterogeneity of Total Factor Productivity in Nine Pan-PRD Provinces in China

As a national regional development strategy and a vital region of the Belt and Road Initiative, the sustainable development of the Pan-Pearl River Delta (Pan-PRD) region is of great importance. The national development plan emphasizes improving total factor productivity (TFP) and promoting high-quality economic development. This paper uses the DEA-Malmquist index model to measure the TFP of nine provinces in the Pan-PRD region based on inter-provincial panel data from 2003 to 2020. Furthermore, it analyzes its growth trend and heterogeneity characteristics in the inter-provincial spatial, industrial, and city dimensions. The results show that in the time dimension, TFP shows a W-shaped fluctuation trend, technical efficiency grows slowly, and technical progress is the pillar of TFP improvement. The spatial dimension shows a high distribution in the center and low distribution in the south. On the industry dimension, the TFP is in descending order as follows: tertiary industry—secondary industry—primary industry. The spatial distribution is heterogeneous, exacerbating the uneven economic development within the region, and the regional industrial structure needs urgent optimization. The spatial development of city TFP is uneven, and the number of cities with a TFP below 1 is increasing. Finally, we suggest policies to accelerate regional collaborative innovation, cultivate advantageous industrial clusters, create an advantageous industrial ecosystem, and achieve sustainable development in the Pan-PRD region.

Synergistic utilization mechanism of e-waste in regions with different levels of development: A case study of Guangdong Province

The overall management of multi-stakeholders in the supply chain, such as consumers, collectors, dismantling enterprises, etc., is the core way to guide regions with different levels of development to form a synergy of e-waste utilization. Based on the complex system theory, this study evaluates e-waste flow trends in regions with different levels of development, and constructs a regional e-waste synergistic utilization model. We employ Guangdong Province, the most typical urban-rural dual structure, as a case study and explore the interplay of stakeholders in the supply chain and strategies for synergistic utilization of e-waste. It is found that e-waste in the developed areas will spontaneously flow to areas where dismantling and utilizing are highly concentrated. And stakeholders influence the e-waste recycling chain in terms of e-waste dismantling and utilizing and regional environmental performance. The simulation results show that Guangdong Province will still have a large demand for e-waste treatment, and the regional environmental loss will be obvious in 2030. Furthermore, we construct three policy scenarios: strengthening responsibility extension, regional joint prevention and regional collaborative innovation. Under the policy combination, the formal dismantling rate increases by 38.6% and the environmental performance loss ratio decreases by 18%, and the policies have a significant catalytic effect. We further analyze the role of the establishment of an extended responsibility system for producers and consumers, a reverse supply chain traceability system and a regional green circular supply chain system to promote the coordinated development of e-waste.

Spillover and Re-Spillover in China’s Collaborative Innovation

The spillover effect serves as the basis of regional collaborative innovation. Existing research on innovation spillover focuses on the overall impact of a region's innovation factors on local and other regions' innovation activities. However, re-spillover may occur since the flow of innovation factors between any two regions may influence the innovation in third-party regions. This study quantifies labor flow, capital flow, and institutional learning between regions in China using a gravity model and a social network analysis model, and then applies a spatial econometric model to investigate innovation spillover and re-spillover. The results show that re-spillover can better explain levels of regional innovation. Capital, government support, labour flow, capital flow, and institutional learning have a positive spillover effect on local innovation, while labour flow also has positive spillover effects to other regions.

Path optimization of open collaborative innovation of energy industry in urban agglomeration based on particle swarm optimization algorithm

To study the open collaborative innovation path optimization of urban agglomeration energy industry based on particle swarm optimization algorithm. Firstly, this paper brings industrial agglomeration and urban agglomeration into a unified analytical framework, uses location entropy and spatial Gini coefficient to measure the degree of industrial agglomeration, and evaluates the degree of regional industrial agglomeration competitiveness by constructing an evaluation index system of industrial agglomeration competitiveness. Then, the agglomeration index system was established, the development degree analysis method and Carlino model were used to analyze the development degree and agglomeration degree of eco-economic zones, and the agglomeration effect was analyzed by dynamic econometric method and spatial autocorrelation statistical method. Finally, a regional collaborative innovation capability evaluation model based on particle swarm optimization algorithm is constructed. Based on the index system and evaluation model, this paper evaluates and analyzes the collaborative innovation capability, and puts forward countermeasures and suggestions for future collaborative development.

Research on Regional Collaborative Network Innovation and Enterprises’ Innovation Performance in the Sustainable Development of Yangtze River Delta, China

As one of the most dynamic and sustainable economic regions in China, Yangtze River Delta has been forming an innovation cluster of high-quality development. To explore the driving force during the integration of Yangtze River Delta, this article constructs a driving force model and makes an empirical study by the structural equation modeling method. The model proves that heterogeneity knowledge will positively affect innovation, that innovation performance has a strong positive impact on regional collaborative network innovation, that regional collaborative network innovation exerts a positive effect on knowledge spillover, and that organizational learning can affect innovation performance positively. Based on the above research results, some recommendations are proposed. Those recommendations consist of: (a) to forge a dynamic sustainable and innovative regional collaborative network system lay a foundation of high-quality development; (b) while the two driving forces of heterogeneity knowledge and organizational learning activated, the indices of enterprise innovation performance should be optimized.

Improved Intuitionistic Fuzzy Entropy and Its Application in the Evaluation of Regional Collaborative Innovation Capability

Intuitionistic fuzzy entropy is an important concept to describe the uncertainty of intuitionistic fuzzy sets (IFSs). To fully measure the fuzziness of IFSs, this paper comprehensively considers the deviation between membership and non-membership and the influence of hesitation, constructs the general expression of intuitionistic fuzzy entropy based on special functions, and proves some of its major properties. Then, it is verified that some existing intuitionistic fuzzy entropies can be constructed by specific functions. Finally, based on a specific parametric intuitionistic fuzzy entropy, this paper applies it to evaluate the regional collaborative innovation capability, to verify the feasibility and practicability of the entropy. In addition, the effectiveness and practicability of this entropy in decision making are further illustrated by comparing it with other entropy measures.

Exploration on the Construction Path of Cultural Industrial Park in North Anhui from the Perspective of High-quality Development

There exist rich and varied characteristic cultural resources and historical cultural heritages in northern Anhui, and thus, there are advantageous resource conditions for developing the characteristic cultural creative industry. High-quality development strategy brings historical opportunity for the construction of cultural industrial park and the development of cultural and creative industries in Northern Anhui. Cultural industrial park brand building and cultural creative industry development needs to take a characteristic, integrated and coordinated development road. Through characteristic development, the park and cultural and creative industry brand building will be strengthened; through regional industrial linkage and collaborative innovation, the park’s cultural and creative industries will be integrated and coexist; through coordinated development, regional cooperation and innovation will be promoted, supporting the construction of parks and the rapid development of cultural and creative enterprises.

Analysis on Evolution Characteristics and Dynamic Mechanism of Urban Green Innovation Network: A Case Study of Yangtze River Economic Belt

This study puts forward a logical framework for green innovation network analysis, which includes a spatial dimension, a relational dimension, and a systems dimension. Here, we put forward some basic research ideas concerning the optimization and regulation of green innovation networks in terms of the systems dimension and we investigate the micro-dynamic mechanisms of green innovation network expansion using a spatial econometric model. Our main research results are as follows: The efficiency of green innovation in the Yangtze River Economic Belt has improved significantly, however, the gap between cities has gradually increased, and a problem of efficiency regression has emerged. The green innovation network has changed from the primary stage dominated by Edge Network to the rapid growth stage dominated by Supporting Network, and formed a complex network pattern with diversified hierarchical structure. Node symmetry is helpful in forming more extroverted connections and promoting the expansion of green innovation networks. Node proximity and connection symmetry inhibit the growth and development of networks, and knowledge flow cooperation networks can accelerate the evolution of green innovation networks. Finally, this paper holds that we should combine the actual development needs, emphasize the basic principles of differentiated development, and construct the development pattern of regional collaborative innovation. This can also provide a theoretical reference for enriching our understanding of green innovation networks while narrowing the gap between cities.

Retraction Note: Image classification-based groundwater pollution prediction and regional economic collaborative innovation

Retraction Note: Image classification-based groundwater pollution prediction and regional economic collaborative innovation

How financial development scale and R&D influence regional innovation efficiency: empirical evidence from the financial industry.

Financial elements and R&D elements are significant drivers for enhancing regional innovation efficiency. This paper measures financial elements by financial development scale and the marketization level of the financial industry and R&D elements by the inputs and flow of R&D personnel and R&D capital and specifically considers R&D element flow to quantify the consequential spatial spillover effects. Based on provincial panel data from 2008 to 2018, the paper firstly estimates the regional innovation efficiency of China’s 30 provincial-level administrative regions using super-efficiency DEA and then conducts an empirical analysis of the influence of financial elements and R&D elements on regional innovation efficiency by the use of the Tobit model and three spatial econometric models. It is found that, by and large, the financial development scale, the marketization level of the financial industry, the inputs of R&D personnel and R&D capital, and R&D capital flow all have significant effects on regional innovation efficiency. Nonetheless, by region, R&D personnel flow in central China can significantly boost regional innovation efficiency while fails in eastern and western China. From the spatial perspective, both financial elements and R&D elements have significant positive spatial spillover effects. Therefore, in order to bolster regional innovation efficiency, it is crucial to improve the allocation of financial elements and R&D elements and build a tight regional collaborative innovation network.

RETRACTED ARTICLE: Image classification-based groundwater pollution prediction and regional economic collaborative innovation

At present, as a nonrenewable resource, water resource has become an important living condition of human society and the whole ecosystem. As an important part of the whole social water resources system, groundwater resources play a very important role in human society. Due to the scarcity of surface water resources and the aggravation of pollution, human beings began to exploit the relatively clean underground water. In China, groundwater accounts for about one third of all water resources, and is one of the important water sources for people’s living water, social production, and development. At present, many cities in China are using groundwater as industrial and domestic water. Because of the nature of groundwater, when it is polluted, it is difficult to treat and recycle, which directly affects people’s water use and social development. Therefore, we propose a groundwater pollution prediction method based on image classification. Supply chain coordination based on the analysis of the basic principles of regional economic innovation system, this paper focuses on the problems related to the supply chain system coordinated with the development of regional economic innovation. By creating a supply chain system and combining with the characteristics of regional economic development, the decentralized system can be integrated across different regions, departments and companies. In this paper, through the realization of the optimal allocation of production factors resources, to achieve the value reconstruction and create the added value of regional economy and industrial collaborative innovation, effectively promote the healthy and scientific development of China’s social economy.

Spatial Pattern and Benefit Allocation in Regional Collaborative Innovation of the Yangtze River Delta, China

Spatial Pattern and Benefit Allocation in Regional Collaborative Innovation of the Yangtze River Delta, China

Triple helix relationship research on China's regional university–industry–government collaborative innovation: Based on provincial patent data

AbstractOver the last 20 years, university–industry–government collaborative innovation has received extensive attention in theory and practice. However, the question of how to integrate and understand collaborative innovation from a theoretical perspective has not been thoroughly studied. This study designed a regional collaborative innovation evaluation model based on the triple helix theory. The invention patent data of 31 provincial regions in China for the last 5 years are used to investigate the regional differences and dynamic evolution of the collaborative innovation and the interaction and coupling relationship between intraregional and interregional industries, universities, and governments empirically. This study found that the number of invention patents in China has rapidly grown yearly, indicating that industries are the most important source of invention patents. The difference in the regional distribution of China's collaborative innovation output is remarkable, showing a pattern of “strong east and weak west” in the total volume and “south fast north slow” in the growth rate. The bilateral synergistic effect of industry–university relations is strong considering two‐dimensional cooperation, and the relationship is close. Collaborative innovation is dominated by intraregional cooperation, whereas interregional cooperation shows a growing trend. The tripartite relationship between university, industry, and government shows a loose trend. Certain provinces with weak regional innovation capabilities, such as Gansu, Hainan, Xinjiang, and Qinghai, have a relatively close cooperation level, which is in the stage of government‐led innovation and development. However, Guangdong, Chongqing, Anhui, Jiangsu, and other provinces with outstanding regional innovation capability do not have close cooperation between universities, industries, and governments, which are in the stage of innovation and development led by industries. This paper discusses the policy implications for different regions based on the research conclusions.