Level Of Technological Innovation Research Articles

Scoping review on the link between economic growth, decent work, and early childhood caries

BackgroundEarly Childhood Caries (ECC) is a prevalent chronic non-communicable disease that affects millions of young children globally, with profound implications for their well-being and oral health. This paper explores the associations between ECC and the targets of the Sustainable Development Goal 8 (SDG 8).MethodsThe scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. In July 2023, a search was conducted in PubMed, Web of Science, and Scopus using tailored search terms related to economic growth, decent work sustained economic growth, higher levels of productivity and technological innovation, entrepreneurship, job creation, and efforts to eradicate forced labor, slavery, and human trafficking and ECC all of which are the targets of the SDG8. Only English language publications, and publications that were analytical in design were included. Studies that solely examined ECC prevalence without reference to SDG8 goals were excluded.ResultsThe initial search yielded 761 articles. After removing duplicates and ineligible manuscripts, 84 were screened. However, none of the identified studies provided data on the association between decent work, economic growth-related factors, and ECC.ConclusionsThis scoping review found no English publication on the associations between SDG8 and ECC despite the plausibility for this link. This data gap can hinder policymaking and resource allocation for oral health programs. Further research should explore the complex relationship between economic growth, decent work and ECC to provide additional evidence for better policy formulation and ECC control globally.

Disruptive development path measurement for emerging technologies based on the patent citation network

Studying disruptive innovation development paths for emerging technologies helps trace and grasp key core technologies development, promoting innovation and development in emerging technologies and industries. This paper measures the innovation development path for emerging technology, including: (1) improving the triple citation network and quantifying disruptive measurement by designing a technological disruption model; (2) proposing a contraction method for the citation network from the dataset perspective; (3) proposing a method to extract the main path using technology disruption degree as a criterion for citation networks importance; (4) taking the sintering technology in 3-D printing technology as the empirical object with 12,662 patent families from 1997 to 2019. The empirical results indicate that the disruption degree value is determined by the transitive citation relationship without the co-citation relationship, and the closed-loop structures are effectively removed, thereby reducing the size of the dataset. The proposed disruption quantification method can support effective evaluation of technological innovation levels and decision-making for the research and development (R&D) direction and resource allocation.

Exploring the moderating role of digital finance in the two-way foreign direct investment and green technology innovation nexus: an empirical evidence from China.

Based on the provincial panel data of China from 2011 to 2020, this paper explores the relationship between two-way FDI and green technology innovation and examines the moderating role of digital finance in the impact of two-way FDI on green technology innovation. The results show that (1) two-way FDI can significantly enhance the level of green technology innovation. (2) Digital finance plays a moderating effect in the process of two-way FDI to enhance the level of green technology innovation. The conclusion is still robust by replacing the dependent variable, eliminating special samples and shrinking the tail. (3) The results of sub-dimensional analysis show that the three sub-dimensions indicators of the digital finance also have a positive moderating effect on the relationship between two-way FDI and green technology innovation. (4) The results of sub-regional regression show that the moderating effect in the central and western regions is greater than that in the eastern region. The results of the study can provide reference for governments to formulate policies about digital finance, which is conducive to achieve high-quality opening-up and realize green development.

The coordination of technological and financial innovation concepts on the marine economy and its ecological development

This study first constructs an evaluation index system based on the pressure state response model, and assigns weights through entropy method and coefficient of variation method, providing theoretical and methodological support for comprehensive measurement and evaluation. Second, the least squares decision model is introduced and the PVAR model is used to analyze the development level of China's marine economy, ecology, and technological and financial innovation. The results indicated that from 2012 to 2022, the marine economic development level, marine ecological development level, and marine technology and financial innovation development level of 9 coastal provinces in China all showed a certain growth trend. However, in terms of the level of marine ecological development, various provinces had shown a downward trend, with Hebei performing the best, with an average of 0.230. Although various regions have achieved significant development in marine economy, ecology, and technological and financial innovation, the level of development varies among regions, and some regions have relatively low levels of technological innovation. The pressure and challenges between the marine economy and ecological environment protection caused by these real environments remain significant.

Calculation and analysis of the efficiency of resource allocation for technological innovation in China.

The efficiency of resource allocation in technological innovation is a critical factor influencing the output level of technological innovation. By expanding and optimizing the Hsieh & Klenow (2009) framework for analyzing the efficiency of resource allocation and relaxing the assumption of constant returns to scale, this study utilizes sample data from Chinese listed companies from 2007 to 2019 to measure and analyze the resource allocation efficiency level in China's technological innovation. The findings indicate that in the process of technological innovation, companies face heterogeneous resource usage costs, leading to a deviation from the optimal resource allocation state, with evident issues of resource misallocation. The loss of efficiency in technological innovation output due to resource misallocation is significant, and addressing this issue can substantially enhance the level of technological innovation output. The misallocation of research and development capital resources is more severe than that of research and development personnel, resulting in greater efficiency losses in technological innovation output. Government subsidies are identified as a significant factor affecting resource allocation in technological innovation. Addressing the issue of resource misallocation, accelerating the market-oriented reforms of technological innovation resource allocation, and optimizing the government subsidy screening mechanism are crucial for improving the efficiency of resource allocation in technological innovation.

Research on the Influencing Factors and Countermeasures of Cultivating Financial Innovation Talents under the Background of Big Data

Abstract The lack of high-quality financial innovation talents has become an obvious shortcoming in the development of financial innovation, and the call for the cultivation of talents to adapt to the increasingly changing new economic environment has become increasingly urgent. This study extracted the key factors affecting the cultivation of financial innovation talents by preprocessing the relevant data and eliminating the unreasonable information, and used factor analysis to remove the key factors influencing the cultivation of financial innovation talents, and used Pearson’s correlation coefficient method and correlation rule analysis algorithm to analyze the interrelationships between these factors in depth. The analysis results show that the correlation coefficients between the level of economic development and educational background and technological innovation reach 0.69 and 0.58, respectively, while the correlation coefficient between the level of human capital and the level of technological innovation is 0.46. Analyzing the level of financial innovation talent cultivation, we find that financial innovation development grows from about 22.5% to about 37.5% from 2016 to 2023. At the same time the amount of financial innovation talent grows from 490,000 to 880,000 people. However, the growth of financial innovation talent is gradually slowing down, pointing to the urgent need to develop talent. The strategies and suggestions put forward in this study provide essential references for cultivating financial innovation talents in the future, aiming to promote the sustainable development of financial innovation and the optimization of talent structure.

How do enterprises’ green collaborative innovation network locations affect their green total factor productivity? Empirical analysis based on social network analysis

Green collaborative innovation plays an increasingly prominent role in improving enterprises' green total factor productivity (GTFP). Using China's listed manufacturing enterprises' panel data from 2011 to 2022, this paper uses social network analysis to construct green collaborative innovation networks based on the data of joint applications for green patents. This paper then performs an empirical analysis to explore the impact of enterprises' green collaborative innovation network locations on their GTFP and the associated impact mechanism. The results show that (1) enterprises in the core position of a green collaborative innovation network can enhance their GTFP, and this conclusion remains robust after replacing explanatory variables and changing the sample selection scope and the estimation of instrumental variables; (2) differences in green collaborative innovation type, enterprise ownership structure and time stage lead to heterogeneity in the influence of green collaborative innovation network location on GTFP; and (3) enterprises in the core location of a green collaborative innovation network indirectly promote their GTFP through improving their technological innovation level and resource allocation efficiency. This paper provides a practical and feasible path for the promotion of GTFP and high-quality economic development from the perspective of a green collaborative innovation network.

Research and application of carbon emission data sharing model based on privacy computing

In the context of the dual-carbon goal, improving the level of scientific and technological innovation of modern carbon emissions and achieving comprehensive green development are not only one of the trends and important reform directions of today’s world development, but also the core content of achieving sustainable development. Taking the power industry as an important breakthrough, this paper uses blockchain technology and privacy computing technology to integrate data from the government, power grid, taxation and banks, and proposes a blockchain-based privacy computing algorithm for carbon emission scores to create an execution environment for trusted sharing of carbon emission data, expand channels for carbon emission data collection, and give full play to the value of big data on carbon emissions. Promote the realization of dual carbon goals as soon as possible.

Research on the enhancement path of green technology innovation efficiency under the group perspective.

China is at a critical moment of transforming high-speed development to high-quality development, and it is significant to improve the efficiency of green technological innovation. In this paper, under the perspective of two-stage innovation value chain, we construct the evaluation index system of green technology innovation efficiency, adopt the super efficiency SBM model to measure the green technology innovation efficiency of China's high-tech industries, and based on the results obtained, we assume the fuzzy set qualitative comparative analysis method (fs-QCA) based on the group theory to explore the complex causal mechanism and grouping paths of the interaction between enterprises, government and market that affects the green technology innovation efficiency Mechanism and group path. The study results show that (1) enterprise, government, and market are not necessary conditions to influence the efficiency of green technological innovation, and even if a particular party plays a central role, it needs the assistance of other parties. (2) The improvement of green technological innovation efficiency requires the interaction of enterprises, government, and market, and even if any party does not have the core conditions, it can still produce high green technological innovation efficiency. (3) The path of the "innovative compensation" effect is identified, which indicates that enterprises will generate a high level of green innovation efficiency under sufficient investment brought about by the enterprise scale effect and matched with a good level of economic development. (4) The market economy-led pathway suggests that when the market economy is highly developed, firms do not need environmental regulation and government support to generate efficient levels of green technological innovation.

How to promote urban employment in the process of local transformation and upgrading? -- Analysis based on principal component regression

The possible unemployment in the process of industrial upgrading may affect the improvement of residents’ well-being, so it is very necessary to study its influencing factors. Based on time series data from 2000 to 2019, this paper selects indicators that may affect urban labor employment from three dimensions: economic growth, structural change and technological progress, and further analyzes the factors affecting urban labor employment through principal component regression on this basis. The empirical results show that although economic growth factors can also have a positive effect on urban labor employment, its impact is not significant compared with the other two types of factors. Therefore, the government should combine various measures to promote employment, accelerate the transformation and upgrading of industrial structure at the same time, increase investment in independent research and development, improve the level of technological innovation, and should also focus on improving the quality of workers.

The Effects of Technological Innovation on Sustainable Development in Morocco: Does the Transition to Social Innovation Matter?

Technological innovation currently is one of the crucial factors influencing economic growth and contributing to development. However, our primary aim by presenting this paper is not solely the economic progress ensured by innovation, but rather to study the impact of technological innovation on the three pillars of sustainable development (economic, social and environmental). This means that we will examine the repercussions at an economic, social, and environmental level. To do so, we have worked with a time series covering the period from 1990 to 2021 in Morocco, estimated by the ARDL model to figure out short-term and long-term results. Our findings were as follows: concerning the relationship between technological innovation and the economic pillar, it is seen to be positive in the short term and tends to become slightly negative in the long term. Regarding the relationship between technological innovation and the environmental pillar, a positive impact is clear, meaning that an increase in technological innovation levels reduces environmental damage. However, in the long term, this trend may reverse as it tends to become less positive or even negative. Finally, the relationship between technological innovation and the social pillar is characterized as non-significant.

Innovating from the ground up: the impact of key technological advancements on collaborative carbon and haze governance.

Strengthening the synergistic management of carbon and haze is an important means to realize China's "carbon peaking and carbon neutrality goals" and green development. In this paper, the entropy method is used to measure the key core technology innovation level of 30 provinces in China from 2011 to 2021, and the fixed-effect model is used to empirically test the impact of key core technology innovation on carbon haze synergistic governance and the internal mechanism. The study found that (1) key core technological innovation helps to promote carbon haze synergistic governance. (2) The mechanism test shows that key core technology innovation promotes the synergistic management of carbon haze by improving the clean energy structure. (3) The moderating effect shows that both market incentives and government environmental regulations will strengthen the positive relationship between key core technology innovation and carbon haze synergistic governance. The main contribution of this paper is to reveal the influence mechanism of key core technology innovation on carbon haze synergistic governance, and also to provide theoretical basis for the mechanism and law of carbon haze synergistic governance.

Reexamining the impact of financial development on ecological footprint: The roles of population aging, per capita GDP, and technological innovation

Existing research results on the impact of financial development on ecological footprint are inconsistent or even opposite. In order to better understand the impact of financial development on ecological footprint, this study explores the relationship between financial development and ecological footprint from the perspectives of population aging, GDP per capita, and technological innovation. The results show that when the population aging level is below the threshold, the coefficient of financial development on ecological footprint is 0.285, but when the aging level exceeds the second threshold, the coefficient of financial development on ecological footprint becomes faint negative. Similarly, after per capita GDP crosses the threshold, the correlation coefficient between financial development and ecological footprint turns from positive to faint negative. Compared to this, when the level of technological innovation is below the threshold, the coefficient of financial development and ecological footprint is 0.155, while when the level of technological innovation is above the threshold, the coefficient of financial development and ecological footprint is −0.597. The above results indicates that the impact of financial development on the ecological footprint is affected by other factors. Compared with changes in population structure (aging) and social wealth (GDP per capita), technological innovation has a greater impact on the relationship between financial development and ecological footprint.

The effect of foreign aid on carbon emissions in recipient countries: Evidence from China

Foreign aid is an essential tool in economic diplomacy tool, yet its significance in global environment governance often goes underestimated. Taking 118 countries that received Chinese foreign aid from 2000 to 2018 as the research objects, this study investigated the impact of foreign aid on the carbon emissions of recipient countries and the mechanism. Firstly, the present study found that Chinese foreign aid increased the overall carbon emission levels of recipient countries during the sample period, with each 1 % increase in Chinese foreign aid being followed by a 0.0148 % increase in the carbon emissions of recipient countries. Secondly, the improvement of the economic growth and technological innovation of recipient countries served a mediating role in the process of Chinese aid affecting the carbon emissions of recipient countries. Thirdly, the threshold test results indicate that Chinese foreign aid helps to reduce the carbon emission levels of recipient countries when their economic growth rates and technology innovation levels are low, noting that this emission reduction effect may weaken as the recipient countries' economic growth rates and technological innovation increase. The findings of this paper expand the literature on the functional theory and non-economic consequences of foreign aid. Moreover, they told significant theoretical and policy implications for promoting cleaner aid practices and fostering low-carbon, green growth in recipient countries.

The driving factors and spatial evolution of industrial water pollution governance efficiency in the Yangtze River Delta urban agglomeration in China.

In order to explore the effective path to improve the efficiency of industrial water pollution governance efficiency (WGE), this study takes 27 prefecture-level cities in the Yangtze River Delta urban agglomeration in China as the research object, measures WGE through the improved SBM model, and tests the impact of WGE drivers using the spatial Durbin model (SDM). The study found that environmental pollution governance investment (EPGI) is positively correlated with WGE, and industrial agglomeration status (IAS) has inhibitory effects on the improvement of WGE. By testing IAS2, it was determined that the impact of IAS on WGE has a "U"-shaped relationship. The direct impact of EPGI on WGE is 0.5016, and the indirect impact on WGE is 0.6428; the direct impact of IAS on WGE is -0.3036, and the indirect impact on WGE is -0.5158. Among the other tested impact drivers, per capita GDP (PCG), industrial structure (IS), and level of technological innovation (TIL) are positively correlated with the dependent variable WGE, while energy consumption intensity (ECI), environmental regulation intensity (ERI), and degree of openness to foreign investment (FIR) are negatively correlated with the dependent variable WGE. In addition to the impact of the aforementioned main drivers, IAS and EPGI, these six drivers also largely influence and determine the final impact on WGE.

Unlocking the role of smart cities in technological innovation: evidence from China

ABSTRACTThis paper discusses the impact of smart city on technological innovation and the underlying mechanism. Based on county-level panel data in China from 2005 to 2020, we use the ‘smart city’ construction as a quasi-natural experiment to identify its impact on technological innovation. Our findings show that: (1) Smart city construction significantly promotes technological innovation. (2) Smart cities indirectly promote technological innovation through technology resource allocation, industry agglomeration effects, and entrepreneurial spirit. (3) Due to ‘digital divide’, the innovation effects of smart cities are more pronounced in eastern regions and cities with high levels of digital infrastructure and information technology talent endowment. (4) The ‘smart city’ pilots generate spatial spillover effects, which enhance the technological innovation level of neighbouring cities.

Artificial intelligence-driven bioenergy system: digital green innovation partner selection of bioenergy enterprises based on interval fuzzy field model

PurposeThe aim of this study is to (1) construct a standard framework for assessing the capability of bioenergy enterprises' digital green innovation partners; (2) quantify the choice of partners for digital green innovation by bioenergy enterprises; (3) propose based on a dual combination empowerment niche digital green innovation field model.Design/methodology/approachFuzzy set theory is combined into field theory to investigate resource complementarity. The successful application of the model to a real case illustrates how the model can be used to address the problem of digital green innovation partner selection. Finally, the standard framework and digital green innovation field model can be applied to the practical partner selection of bioenergy enterprises.FindingsDigital green innovation technology of superposition of complementarity, mutual trust and resources makes the digital green innovation knowledge from partners to biofuels in the enterprise. The index rating system included eight target layers: digital technology innovation level, bioenergy technology innovation level, bioenergy green level, aggregated digital green innovation resource level, bioenergy technology market development ability, co-operation mutual trust and cooperation aggregation degree.Originality/valueThis study helps to (1) construct the evaluation standard framework of digital green innovation capability based on the dual combination empowerment theory; (2) develop a new digital green innovation domain model for bioenergy enterprises to select digital green innovation partners; (3) assist bioenergy enterprises in implementing digital green innovation practices.

How can new energy development reduce CO2 emissions: Empirical evidence of inverted U-shaped relationship in China.

This article is based on the statistical yearbook data of 30 provinces, municipalities and autonomous regions in China (excluding Hong Kong, Macao, Taiwan, and Tibet Autonomous Region) from 2000 to 2017, a total of 18 years of statistical yearbook data was used to conduct in-depth research on the reduction of CO2 emissions from the development of new energy in the region. First, it is proposed that the regional new energy development has a significant negative effect on CO2 emissions. Meanwhile, this impact has a significant time lag effect, and the development of new energy cannot be quickly and effectively applied in the short term to replace traditional fossil energy in the dynamic model. Therefore, there is a significant positive impact in the short term, but the significant negative effect of new energy development on CO2 emission can be shown in the long run. Secondly, the new energy development has a significant non-linear impact on CO2 emissions, showing an inverted U-shaped relationship, which confirms the existence of the Environmental Kuznets Curve (EKC) of CO2 emissions based on new energy development. Finally, in order to alleviate the continuous impact of national economic development on CO2 emissions, the DID model is used to prove that the level of technological innovation has a significant moderating effect on the CO2 emission reduction effect of new energy development, which confirms theoretically the importance of technological innovation in accelerating new energy substitution and improving energy efficiency.

Impact of industrial robots on environmental pollution: evidence from China

The application of industrial robots is considered a significant factor affecting environmental pollution. Selecting industrial wastewater discharge, industrial SO2 emissions and industrial soot emissions as the evaluation indicators of environmental pollution, this paper uses the panel data model and mediation effect model to empirically examine the impact of industrial robots on environmental pollution and its mechanisms. The conclusions are as follows: (1) Industrial robots can significantly reduce environmental pollution. (2) Industrial robots can reduce environmental pollution by improving the level of green technology innovation and optimizing the structure of employment skills. (3) With the increase in emissions of industrial wastewater, industrial SO2, and industrial dust, the impacts generated by industrial robots are exhibiting trends of a “W” shape, gradual intensification, and progressive weakening. (4) Regarding regional heterogeneity, industrial robots in the eastern region have the greatest negative impact on environmental pollution, followed by the central region, and the western region has the least negative impact on environmental pollution. Regarding time heterogeneity, the emission reduction effect of industrial robots after 2013 is greater than that before 2013. Based on the above conclusions, this paper suggests that the Chinese government and enterprises should increase investment in the robot industry. Using industrial robots to drive innovation in green technology and optimize employment skill structures, reducing environmental pollution.

Does Low-Carbon City Construction Promote Integrated Economic, Energy, and Environmental Development? An Empirical Study Based on the Low-Carbon City Pilot Policy in China

Low-carbon urban transformation is considered the path to green economic growth in dual-carbon contexts. The low-carbon city pilot policy (LCCP) in China has vast potential to enhance the integrated development of the economy, energy, and environment (3Es). Taking 240 cities in China from 2005 to 2019 as research samples, this paper investigated the impact of LCCP on the integrated development level of the 3Es using the progressive difference-in-differences model and analyzed the mechanisms of influence. In addition, the implementation effects on different cities were analyzed using the triple difference model. The findings show that implementing the LCCP policy significantly improves the 3Es integrated development level in the sample cities, and a variety of robustness tests were used to validate this conclusion. The influence mechanism analysis shows that the primary avenues for pilot programs to contribute and successfully advance the enhancement of the low-carbon city 3Es integrated development level are technological innovation and financial development. Moreover, the heterogeneity analysis of resource endowment and geographical location shows that LCCP is beneficial to the 3Es integrated development in non-resource-based cities and eastern cities. Consequently, policy recommendations include the continuation of low-carbon pilot city expansion, joint promotion of regional 3Es integration, improving the level of technological innovation and financial development, and tailoring of policy to local circumstances. This study provides theoretical support for the evaluation of China’s LCCP and, to a certain extent, proves that the measures taken by China in the process of exploring green economic growth and realizing the dual-carbon goal are correct.