High-tech Industries In China Research Articles

From green finance to sustainable innovation: how to unleash the potential of China's high-tech industry.

Green finance is acknowledged as a critical policy tool in China's sustainable development sector, with the goal of lowering the financial burden associated with ecological transformation for Chinese firms. This research examines the impact of green finance on the green innovation efficiency of the high-tech industry in China, within the context of carbon neutrality. Using a panel dataset covering 30 provinces, autonomous regions, and municipalities in China from 2013 to 2021, we analyze the effects of green finance on green innovation efficiency. Our findings indicate that green finance significantly improves the green innovation efficiency of the high-tech industry, even after robustness testing. Furthermore, this paper also explores the threshold effect of industrial agglomeration on the relationship between green finance and green innovation efficiency, specifically in terms of specialization, diversity, and competition. We verify that green finance reduces the costs of green transformation for enterprises, leading to a substantial improvement in the green innovation efficiency of the high-tech industry. These results shed light on the factors influencing green innovation efficiency and provide theoretical insights and implications for policymakers, entrepreneurs, and financial institutions to reconcile economic growth and sustainability goals.

Does spatiotemporal heterogeneity matter? Air transport and the rise of high-tech industry in China

Air transport has essential effects on economic landscapes. However, geographical issues, such as spatiotemporal heterogeneity, still lack full discussion. To fill this gap, our research built a multiscale geographically and temporally weighted regression (MGTWR) model with the help of panel data from 35 large and medium-sized cities in China during 2003–2017. The findings are as follows. First, a 1% increase in air transport passengers has resulted in a 0.1% growth in innovation performance in the high-tech industry. Second, these impacts showed spatiotemporal heterogeneity. Effects in Southwest China were valued higher than in other parts of China, and the results performed better as time progressed. Third, air transport was more global and long-term than other related factors, which provides a reference for significant changes in spatial and temporal intervals when doing the planning. These findings broaden our understanding of global and local associations between air transport and regional innovation.

How to Improve the Synergetic Development Capabilities of the Innovation Ecosystems of High-Tech Industries in China: An fsQCA Analysis Based on the TOE Framework

This study explores the synergetic development capability of China’s high-tech industry innovation ecosystem and the diversification path necessary to improve it. Based on the four-spiral perspective, the system synergetic development index was constructed, and the composite system collaborative degree model was used to measure the synergetic development capability of the high-tech industry innovation ecosystem across 30 provinces and cities in China from 2012 to 2020. The influencing factor model of improving the system’s synergetic development capability was constructed under the technology–organization–environment (TOE) framework, and a fuzzy set qualitative comparative analysis (fsQCA) method was used to explore the multiple paths available to improve the synergetic development ability of the system. The results show that the four-helix system’s synergetic development capability is poor and needs to be improved. The “technology–organization–environment” conditions cannot be used alone as the necessary conditions for the improvement in the system’s synergetic development capability but need to exert a joint, matching effect through the combination of different factors. In addition, market openness is crucial on the path toward the highly synergetic development of the system. The research results not only provide a theoretical basis for comprehensively improving the system’s synergetic development capability but also provide a practical reference for the differentiation path being revealed. In short, this study has important theoretical and practical significance to promoting the synergetic development and benign evolution of the high-tech industry innovation ecosystem.

The Nexus between Foreign Competition and Buying Innovation: Evidence from China’s High-Technology Industry

This study aims to investigate how international competition impacts innovation activities in the high-technology industry in China. A panel data analysis was conducted using a representative sample of high-tech industries in China from 2010 to 2017. Econometric methods were used to identify patterns and trends in the data, and quantile regression was utilized to explore the delicate connection between international competition and innovation efforts. The statistical analysis indicates that the effect of international competition on innovation activities differs through dependent quantiles of the innovation range; this effect was neglected by a standard linear regression model. The study found a U-shaped connection between foreign competition and innovation, except for at the quantile (Q = 0.01), which was negative. Foreign competition was found to be a critical factor influencing the strength of innovation activities in the high-tech industry in China. This research suggests that the extent of foreign competition has a bearing on the industry’s capacity to lead in innovation. This study is unique in that it addresses the influence of international competition on industry-level innovation accomplishments in a big rising country, such as China. The study also highlights the importance of evaluating the quantile effect of the variable on innovative activities, which was more informative than estimating the mean effect. The study’s limitation lies in the reliance on secondary data sources, which may not be as comprehensive as primary data. The research’s implications suggest that policymakers should pay attention to the impact of foreign competition on innovation activities and implement policies that foster innovation in the high-tech industry in China.

Multinational Corporations and Technological Innovation Development of China’s High-Tech Industries: A Heterogeneity-Based Threshold Effect Analysis

Technological innovation of multinational corporations (MNC) is an important engine to drive the world’s scientific and technological progress, which plays an important role in the sustainable development of global innovation. With China’s high-tech industry from 2009 to 2020 as the research sample, this study empirically analyzes the impact of MNCs’ two-stage innovation on the innovation efficiency of China’s high-tech industry through the perspective of base regression, threshold effect, and regional heterogeneity. It was found that MNC research and development (R&D) efficiency and achievement transformation efficiency have a positive impact on the innovation efficiency of high-tech industries in China, with nonlinear features and regional heterogeneity. This study provides an empirical basis for the efficient use of MNC’s innovative resources and the sustainable development of China’s high-tech industry.

The Impact of Financial Services on Import and Export Trade of the High-tech Industries in China

The Impact of Financial Services on Import and Export Trade of the High-tech Industries in China

Potential of Passive Employees: How Servant Leadership Can Stimulate Innovation among Control-Oriented Employees

Depending on the organizational context, a control orientation on the part of an employee may either inhibit or promote their innovative job performance. To explore the question of which external conditions are conducive to control-oriented employees’ innovative potential, this study examined the effects of servant leadership on control-oriented employees’ motivation internalization processes and innovative job performance from a self-determination theory perspective. This study was conducted in Jiangsu, Shanghai, and Anhui provinces, which are relatively developed high-tech industries in China. An analysis of paired data from 298 employees and their leaders in nine technology-intensive companies revealed that servant leadership plays a positive moderating role between control orientation and employees’ autonomous motivation. Moreover, the interaction between control orientation and servant leadership can affect innovative job performance through the mediation of identified regulation, but not through that of integrated regulation. These findings are beneficial in promoting healthy development and innovative job performance of control-oriented employees, and are instructive for sustainable human resource management. Organizations should recognize the creative potential of control-oriented employees, promote servant leadership, leverage its management strengths, and focus on enhancing employees’ sense of identification with their jobs.

Spatial and Temporal Patterns of China's High-Tech Industries and Structural Decomposition of Sources of Spatial Variation: 2012-2020

This paper investigates the spatial distribution of high-tech industries in China and the structural decomposition of their sources of spatial variation from 2012 to 2020. The results are visualized by using ArcGis plotting. And the Thiel index is used to quantitatively analyze the overall regional differences, intra-zone differences and inter-zone differences, as well as the contribution rate of intra-zone differences and inter-zone differences to the overall differences in China's high-tech industry from 2012 to 2020. China's high-tech industry is characterised by uneven development within the Eastern, Western, Central and Northeastern Regions. Especially within the Western Region, the development is very uneven. It is recommended to introduce high-tech talents to the less developed areas of high-tech industry; to provide stronger policies to help the local high-tech industry; to further divide the Western Region into developed and less developed areas of high-tech industry in the west, and to provide more precise assistance.

Financial system and technology innovation in an emerging economy: can innovation efficiency be increased?

PurposeThis study aims to investigate the influence of the financial system (financial development and financial structure) on firms' innovation efficiency in China.Design/methodology/approachThis study employs country level data of capital markets and financial institutions along with innovation data from 18 high-tech industries in China spanning the 2009–2016 period, and the stochastic frontier analysis (SFA) is applied to explore how financial development and financial structure affect the innovation efficiency of these industries.FindingsResults show that financial development influences firms' innovation efficiency positively and the capital-market-based financial structure has a positive impact on innovation efficiency of high-tech industries. Furthermore, when the high-tech industries are grouped into five sub-industries, the results show that financial structure had different effects on the innovation efficiency in each sub-industry.Originality/valueThis work contributes to the empirical research on considering the influential factors of innovation efficiency from the perspective of financial system. This paper also extends the existing literature by the different influences of financial system on innovation efficiency in each sub-industry of Chinese high-tech industries.

Quantitative Evaluation of High-Tech Industry Policies Based on the PMC-Index Model: A Case Study of China’s Beijing-Tianjin-Hebei Region

High-tech industrial agglomeration plays a significant role in regional sustainable development. Local governments have issued many industrial policies to accelerate the development of high-tech industries in China. Evaluating high-tech industry policies from the perspective of regional industrial synergy can prevent problems in policy implementation and promote the industrial synergy in a region. For this purpose, taking China’s Beijing-Tianjin-Hebei (BTH) region as a case, we evaluate seven policies governing the high-tech industry in this region by using the approach which integrates the policy modeling consistency index (PMC-Index) model and text mining. We propose an evaluation system with consideration of regional industrial synergy, which is based on the PMC-Index model. The results show that the lowest PMC-Index value of the seven policies is 5.30, the highest is 8.17, and the average is 6.67. Among the policies, four are of excellent or perfect grade and relatively comprehensive; three are of acceptable grade and relatively insufficient. The overall designs of the high-tech industrial policies are reasonable but there is still much room for improvement. According to the average scores of the main indicators, the policies function relatively poorly in terms of policy release agency, policy timeliness, policy type and policy receptor. The optimizations for the shortcomings of each policy are also suggested. This study may not only provide some enlightenment to policymakers, but also provide a supplement for the policy evaluation field.

Forecasting the economic indices of the high-tech industries in China using the grey multivariable convolution model

Reliable output forecasts are critical for decision-making and planning in high-tech industries. Several endogenous and exogenous factors could influence the output dynamics, and thereby a univariate model that only incorporates historical data and single method improvement is typically insufficient to generate accurate projections. In this paper, a novel grey multivariable convolution model is designed from a collaborative optimization perspective. The core innovations of this study can be summarized as follows. Initially, a collaborative framework integrating background value optimization, data preprocessing, and model structure improvement is constructed, which overcomes the internal deficiencies of the conventional grey models. Secondly, the Particle Swarm Optimization algorithm is selected to determine the optimal values of the damping accumulation parameters to enhance the adaptability and flexibility of the proposed model. Further, for validation purposes, experiments on forecasting the output of high-tech industries considering R&D investments are conducted from the national and provincial levels, among which six competing models are involved. Moreover, Monte-Carlo Simulation, incorporated with probability density analysis and statistical analysis, is introduced to evaluate the robustness of the newly-designed model. It can be demonstrated from the empirical results that the novel model is a reliable and promising method for predicting the economic indices of the high-tech industries with enhanced forecasting capability.

Impact of local living environment on innovation efficiency of high-tech industries in China: a spatial analysis.

Environmental problems not only relate to residents' happiness but also challenge the innovation development of industries. This study first measures the innovation efficiency of China's high-tech industries using the super-efficiency data envelopment analysis model and portrays its spatial characteristics through the Moran's I index and the local indicators of spatial association map. Second, we use the entropy weight method to construct the local living environment index from both natural and social environments. Finally, we utilize spatial econometric models to analyze the impact of local living environment on high-tech industries' innovation efficiency. The results reveal that, first, the spatial variation of innovation efficiency in China's high-tech industries is significant, with efficiency being higher in the east than the Midwest, and higher in the south than the north. Second, innovation efficiency has a positive adjacent and geographical spatial autocorrelation, and low-low agglomeration and low-high agglomeration dominate the types of spatial correlation. Finally, the contribution of the local living environment to the innovation efficiency of high-tech industries is positive and significant. This contribution has an obvious spatial spillover effect and regional heterogeneity. This study can help regional governments to improve local living environments and promote industrial innovation and development.

Effects of innovation efficiency of high-tech industries on CO2 emissions in China: A spatial Durbin econometric analysis.

As a responsible country, China should take on heavy responsibility of energy conservation and emission reduction, and it is an inevitable choice for China to develop high-tech industries and improve the innovation efficiency of high-tech industries in order to alleviate the current environmental pressure. Therefore, this paper takes the panel data of 30 provinces in China from 2005 to 2016 as the research sample, on the basis of using DEA Global-Malmquist index to measure the innovation efficiency of high-tech industries, it constructs three spatial weight matrices, by including spatial geography, spatial economic geography nesting and innovation, and then it uses Spatial Durbin Model to empirically analyze the effect of innovation efficiency of high-tech industry on CO2 emissions in China from spatial perspective. The results indicate: firstly, in China, CO2 emissions gradually increase from 2006 to 2012, however, some provinces have declined after 2012. And CO2 emissions present a descending trend from eastern coastal area to central and western region. Secondly, affected by “warning effect”, CO2 emissions show a significant negative spatial spillover effect. Thirdly, the overall level of innovation efficiency of high-tech industries in China is not high, and its impact on CO2 emissions is not a simple linear relationship, but shows an “inverted N–shaped” curvilinear relation, and its decomposition index EC and TC also have similar characteristics. Obviously, the research in this paper provides a necessary theoretical support for China and some emerging developing countries to rational formulating and effective implementing the energy conservation and emission reduction policies.

The Green Innovative Power of Carbon Neutrality in China: A Perspective of Innovation Efficiency in China’s High-Tech Industry Based on Meta-Frontier DEA

The high-tech industry plays a crucial role in reducing carbon emission and achieving green economic development. This research uses Meta-Frontier data envelopment analysis to measure the innovation efficiency level of the high-tech industry in China’s provinces from 1999 to 2018, compares the difference in this industry’s innovation efficiency under the regional Frontier and common Frontier, and inspects the convergence condition of its innovation efficiency in the three major areas of eastern, central, and western China. The results show under the regional Frontier that the difference in innovation efficiency of the western region’s high-tech industry is the biggest, while the difference in the central region is the smallest, and under the national common Frontier the innovation efficiency level of the eastern region’s high-tech industry is the highest, while that of the western region is the lowest. The regional pattern of innovation efficiency in the high-tech industry is consistent with the development trend of the regional economy. Moreover, by using the ratio of the technology gap ratio, we find that the eastern region has the potential optimal technology in China, whereas the central and western regions have large room for improvement. Lastly, the stochastic convergence test shows that the innovation efficiency of the central region’s high-tech industry presents a convergence trend, but the same trend does not occur in the western and eastern regions as well as for the whole country.

Analysing the impact of high-tech industry on regional competitiveness with principal component analysis method based on the new development concept

PurposeThis study explores how to develop high-tech industries in Hunan province and enhance regional competitiveness. Through the comprehensive quantitative analysis of the development status of the high-tech industry in Hunan province, this paper provides a reference for the development of the high-tech industry in China and the world.Design/methodology/approachThis study constructs a comprehensive evaluation index system of regional competitiveness in Hunan province from the five dimensions of innovation, coordination, green, openness and sharing of the “new development concept.” Through the screening and analysis of relevant economic indicators in Hunan province from 2011 to 2020, the principal component analysis method is used to measure the five development dimensions, verify the hypotheses in the study and finally draw the conclusion.FindingsHunan's high-tech industry is positively correlated with Hunan's regional innovation development competitiveness, regional coordinated development competitiveness, regional green development competitiveness, regional open development competitiveness and regional shared development competitiveness. Among them, the promotion effect on innovation development is the best, followed by the promotion effect on green development, coordinated development and shared development dimension. In contrast, the promotion effect on the open development dimension is relatively weak.Research limitations/implicationsThe statistical data selected in this study have certain timeliness. At the same time, the current economic environment is affected by the new corona pneumonia epidemic, showing specific particularity. In this context, it is bound to cause changes in the impact of high-tech industries on regional competitiveness. In addition, this paper studies the regional competitiveness of Hunan's high-tech industry from a macro perspective. Although relevant studies are conducted from five dimensions, there is a lack of micro-level research.Social implicationsFrom five aspects of the new development concept, this study provides suggestions for developing high-tech industries in Hunan province and even China and the path to enhance regional competitiveness.Originality/valueUp to now, no article measures regional competitiveness with the five development dimensions of new development: innovation, coordination, green, openness and sharing, and quantitatively analyses regional competitiveness on this basis.

Performance evaluation of the Chinese high-tech industry: A two-stage DEA approach with feedback and shared resource

<p style='text-indent:20px;'>The operational process of high-tech industry can be separated into a research and development stage (RDS) and a commercialization stage (CS). Within this, the research employees are shared by both stages, and part of the economic output of the CS becomes a feedback factor and continuously flows back to the RDS. Using this framework, this study establishes cooperative and non-cooperative two-stage data envelopment analysis (DEA) models to explore the efficiencies of regional high-tech industries in China. The proposed approach can calculate the overall efficiency and stage efficiencies simultaneously. Based on empirical data of high-tech industries in 29 regions of China from 2012 to 2016, it is concluded that (1) a harmony exists between the RDS and the CS in the cooperative case, while a disharmony happens between the RDS and CS in the non-cooperative case; (2) there exist distinct geographic characteristics regarding the stage inefficiencies of these regional high-tech industries.</p>

Evaluation on financial support efficiency of new generation high-tech industry in China

From the perspective of enterprises and regions, this paper selects the relevant data of 192 listed companies in China from 2015 to 2019, establishes a static analysis model DEA to evaluate the pure technical efficiency, scale efficiency and comprehensive efficiency of the new generation of high-tech industry financial support; At the same time, the dynamic analysis model DEA Malmquist is established to evaluate the change of financial support efficiency of the new generation of high-tech industry. The results show that: at the enterprise level, the overall efficiency of financial support is still at a low level, and the development is not stable, but the overall performance of the enterprise is good in the technical efficiency of financial support, and there is great volatility in the scale efficiency. At the regional level, the eastern region is the best in both the static and dynamic aspects of financial support efficiency, the western region is the second in the static aspect, and the central region is the second in the dynamic aspect. However, the development trend of the three regions is the same, that is, fluctuating development, and the overall trend is good.

Comparative analysis of total factor productivity in China's high-tech industries

The high-tech industry is a high-end component of the modern industrial system, and the key to high-quality development is to improve total factor productivity (TFP). This article divides the innovation process of the high-tech industry into two sub-stages: technology development and economic conversion. Based on the panel data of high-tech sectors, Malmquist and Hicks-Moorsteen indices are applied to measure the productivity changes. Furthermore, the index decomposition dissects the technological change rate and technical efficiency change, thereby identifying the main factors affecting the productivity change. The results show that the TFP of high-tech industries in China and various regions is upward. From the perspective of each region, the main growth driver in the national and Eastern regions is technological progress, while that in the Central and Western regions is mainly technical efficiency changes. In addition, in terms of each sub-stage, the main growth driver in the technology development stage is technical efficiency change, while in the economic conversion stage and the overall system, technological progress is the primary growth driver.

Path for China's high-tech industry to participate in the reconstruction of global value chains

With the deepening of the international division of labor, the change of the national interest distribution pattern, and the spread of de-globalization in some developed countries, the Global Value Chains (GVCs) are undergoing a new round of large-scale restructuring, and the situation of GVCs being dominated by developed countries is changing. Industries of different countries have different paths of participation in the reconstruction of GVCs, including active embedding in GVCs, constructing National Value Chains, and leading to the creation of Regional Value Chains (RVCs). Different high-tech industries in China choose different ways to participate in reconstruction of GVCs due to their different levels of competitiveness. Based on the Value-Added Revealed Comparative Advantage index, this study constructs the basis and criteria for choosing the path of reconstruction of GVCs and designs the appropriate path for Chinese high-tech industry. Pharmaceutical manufacturing and transportation equipment manufacturing industry tend to constructing National Value Chains against the background of globalization, and the chemical products manufacturing, electrical and electronic equipment manufacturing, and optical equipment manufacturing industries tend toward “indigenous innovation” while dominating the RVC reconstruction path, integratinging global and domestic Value Chains, to achieve the domestic and international double cycle goals.

The Influencing Factors of Financial Support Efficiency of New Generation High-Tech Industry in China: Evidence from Listed Companies

In order to improve the financial support efficiency of new generation high-tech industry in China, from the perspective of the subject (enterprise) in which financial resources were invested, this paper selected 192 listed companies in quantum communication and artificial intelligence concept plates in Chinese stock market as samples. Based on the original data of 2015-2019, the influencing factors of financial support efficiency of new generation high-tech listed companies were then empirically analyzed by using DEA-BCC model and Tobit model. The results showed that the ownership concentration, executive compensation and regional digital inclusive finance level were main factors affecting the financial support efficiency of new generation high-tech listed companies, followed by the technological innovation capability and regional economic development level. However, the influence of growth and comprehensive leverage were limited, and the influence of profitability and capital structure were not obvious. Accordingly, the main countermeasures to improve the financial support efficiency of new generation high-tech industry were proposed, which included giving full play to the advantages and potential of digital inclusive finance, actively guiding enterprises to innovate management, improve quality and efficiency, etc.